IoT: CISA Infographic - Communities Risks & Mitigations

 Below are two informative info-graphics from the Cybersecurity and Infrastructure Security Agency (CISA). They depict the IoT risk landscape and IoT device data flow.

https://www.cisa.gov/sites/default/files/2024-12/PDM24069_CCI_IoT_Device_Risk_and_Mitigation_Infographic_Final_508.pdf 

 

 

IoT Devices: A Growing Security Challenge

Internet of Things (IoT) devices are central to how organizations deliver services and manage infrastructure. As devices proliferate, they expand the digital attack surface. Data from Verizon’s 2024 Mobile Security Index report indicates that 70% of public sector respondents said their organization had experienced a security incident involving a mobile or IoT device (Verizon, 2024). These endpoints are no longer peripheral risks—they are often at the center of modern cyber incidents.

Even organizations that have not yet experienced a known incident face serious challenges managing their IoT systems. Devices are frequently deployed across departments and facilities, added rapidly to support new initiatives, and not always inventoried or governed by consistent security standards. The result is classic “device sprawl”: too many devices, in too many places, with too little centralized visibility. For the public sector, where systems often support critical services, this sprawl can translate directly into operational and safety risks.

To respond, users need to treat mobile and IoT security as a core element of their cybersecurity posture. That means maintaining asset inventories, enforcing configuration baselines, segmenting networks to limit blast radius, and integrating mobile/IoT telemetry into existing monitoring and incident response workflows. With attacks increasingly targeting these devices, proactive governance can be the difference between a contained incident and a larger crisis.

Reference

Verizon. (2024). 2024 Mobile Security Index (MSI). Verizon.

IoT: Cyberthreats to Automatic Tank Gauge (ATG) Systems

Automatic tank gauge (ATG) systems are a cybersecurity concern because they are often internet-connected industrial control systems that monitor fuel storage, leak detection, and tank inventory at gas stations and other critical facilities (BitSight, 2024; Dutch Institute for Vulnerability Disclosure [DIVD], 2025). Reporting in 2026 indicates that attackers have actively targeted exposed ATG systems in the United States, reinforcing long-standing warnings from researchers that these devices can be manipulated when they are placed online without adequate access controls (Energy Marketers of America, 2026; In Food & Fuel, 2026).

What is an Automatic Tank Gauge (ATG)?

An automatic tank gauge is an electronic monitoring system used to measure fuel levels, detect leaks, and support inventory management in underground or aboveground fuel storage systems (U.S. Environmental Protection Agency [EPA], n.d.; DIVD, 2025). In practice, ATGs help operators track tank conditions and support release detection obligations that are part of underground storage tank compliance and environmental protection programs (EPA, n.d.).

Who Controls ATGs?

ATGs are generally controlled by the owners and operators of fuel storage systems, such as gas stations, convenience stores, fuel distributors, and operators of facilities that store petroleum or hazardous substances (EPA, n.d.). State, territorial, tribal, and federal regulators do not typically operate the devices directly, but they regulate the broader underground storage tank environment and compliance expectations surrounding release detection and environmental protection (EPA, n.d.). Vendors, service contractors, and remote monitoring providers may also play a role when they install, configure, maintain, or remotely access the systems (DIVD, 2025; Veeder-Root, 2024).

How Many ATGs Are There in the United States?

A precise national count of ATG devices in the United States is uncertain. The EPA states that approximately 542,000 underground storage tanks nationwide store petroleum or hazardous substances, but that figure refers to tanks rather than ATG units, and one facility may have multiple tanks while not every tank count translates directly into a one-to-one ATG count (EPA, n.d.). The closest verifiable contextual figure is the EPA’s estimate of approximately 542,000 underground storage tanks in the United States (EPA, n.d.).

What Are the Vulnerabilities of ATGs?

The clearest recurring vulnerability is direct exposure of ATG interfaces to the public internet without proper authentication or network isolation (DIVD, 2025; BitSight, 2024). DIVD reported that exposed systems from multiple manufacturers, especially certain Veeder-Root models, could be accessed through serial interfaces commonly reachable on TCP port 10001, allowing unauthorized parties to view fuel levels, change tank labels, alter alarm thresholds, and modify monitoring parameters (DIVD, 2025). BitSight reported multiple critical vulnerabilities across six ATG systems from five vendors and warned that internet-exposed ATGs remain attractive targets for sabotage and cyberwarfare scenarios (BitSight, 2024).

Other weaknesses include poor password practices, insecure remote connectivity, weak segmentation between operational technology and business networks, and overreliance on remote polling designs that require open network paths into the ATG environment (DIVD, 2025; PAS, 2025). Veeder-Root’s guidance also emphasizes controls such as firewalls, access restrictions, and secure remote connectivity, which indirectly confirms that misconfiguration and unnecessary exposure are central risk factors (Veeder-Root, 2024).

What Are the Threats to ATGs?

The threat landscape includes unauthorized access, reconnaissance, tampering, denial-of-service activity, and operational disruption (DIVD, 2025). Researchers and industry alerts have described attackers changing passwords, modifying system information, deleting data, and interfering with remote access and fuel operations when gauges are exposed online (In Food & Fuel, 2026; DIVD, 2025). In addition to opportunistic criminal exploitation, researchers have warned that ATGs could be targeted in sabotage or cyberwarfare contexts because they are part of the fuel distribution ecosystem and are present at critical facilities beyond retail gas stations (BitSight, 2024; DIVD, 2025).

What Harm Could Come from a Cyberattack on an ATG?

Potential harm from an ATG cyberattack includes environmental damage, operational shutdowns, business interruption, false inventory readings, disabled alarms, and impaired leak detection (BitSight, 2024; DIVD, 2025). BitSight reported that attackers may be able to change critical parameters such as tank geometry and capacity, disable alarms, and interfere with automatic or manual responses, creating the possibility of fuel leaks, safety incidents, and economic losses (BitSight, 2024). Industry reporting in 2026 also described incidents in which stations could not pump gas until affected devices were reset or restored, showing that even attacks short of physical damage can disrupt daily commerce and fuel availability (In Food & Fuel, 2026).

Who Would Want to Threaten an ATG and Why?

Several categories of adversaries could have an interest in ATG systems. Cybercriminals may target them for disruption, extortion, vandalism, or opportunistic exploitation of poorly secured systems (DIVD, 2025; In Food & Fuel, 2026). Nation-state or state-aligned actors may view ATGs as a soft target within critical infrastructure, particularly because fuel distribution has economic and public safety significance and ATGs are often locally managed rather than defended through a uniform national architecture (BitSight, 2024; CNN, 2026). Hacktivists or malicious insiders could also target ATGs to cause embarrassment, interrupt fuel sales, or manipulate records and alarms for ideological, retaliatory, or personal reasons, although specific motive patterns vary by incident and are not always publicly confirmed (DIVD, 2025).

What Are the Recent Reports of Attacks on ATGs?

Industry and media reporting from 2026 indicates that attacks against ATGs were not merely theoretical. Energy Marketers of America circulated a cybersecurity advisory in April 2026 stating that known cyberattacks were targeting ATGs in Tennessee and that cybercriminals were targeting systems nationwide, including at least 15 affected tanks at one convenience store chain (Energy Marketers of America, 2026). In Food & Fuel reported that the Utah Department of Public Safety had identified 76 vulnerable ATGs in Utah and more than 4,000 across the United States, while also describing confirmed incidents involving unauthorized access to tank and sensor data, false alarms, and deletion of system information (In Food & Fuel, 2026).

Mainstream reporting also linked the 2026 campaign to suspected Iranian actors. CNN reported that U.S. officials believed Iranian hackers had breached fuel tank monitoring systems at gas stations across multiple states by accessing internet-connected ATGs that lacked password protection (Bertrand et al., 2026). Because attribution in fast-moving cyber incidents can evolve, that point should be treated as a reported government assessment rather than a final judicial finding (Bertrand et al., 2026).

What Measures Should Be in Place to Protect ATGs?

The strongest protective measure is to avoid exposing ATGs directly to the public internet (DIVD, 2025; Veeder-Root, 2024). Recommendations include placing ATGs behind properly configured firewalls, using VPN gateways or dedicated hardware interfaces for remote connectivity, applying source IP filtering, and setting passwords on serial ports where the feature is supported (DIVD, 2025; Veeder-Root, 2024). Operators should also audit their network configurations regularly to identify exposed systems, restrict third-party remote access to only what is necessary, and separate ATG environments from broader corporate or payment networks (DIVD, 2025; PAS, 2025).

Additional protective measures include maintaining documented incident response procedures, validating alarm and leak-detection settings, coordinating with qualified service vendors, and promptly applying vendor guidance or security updates when available (DIVD, 2025; Veeder-Root, 2024). Because some ATG risk stems from insecure deployment rather than a single patchable flaw, sound architecture, restricted connectivity, and administrative discipline remain as important as software maintenance (DIVD, 2025).

References

Bertrand, N., Lillis, K. B., & Marquardt, A. (2026, May 15). Iranian hackers have breached fuel tank readers at gas stations across multiple U.S. states, sources say. CNN. https://www.cnn.com/2026/05/15/politics/iran-hackers-tank-readers-gas-stations

BitSight. (2024, September 23). Critical vulnerabilities discovered in automated tank gauge systems. https://www.bitsight.com/blog/critical-vulnerabilities-discovered-automated-tank-gauge-systems

Dutch Institute for Vulnerability Disclosure. (2025, August 25). DIVD-2025-00005 - Exposed automated tank gauge systems. https://csirt.divd.nl/cases/DIVD-2025-00005/

Energy Marketers of America. (2026, April 13). Urgent cybersecurity advisory: Nationwide cyberattacks targeting automatic tank gauges (ATGs). https://www.fueliowa.com/latest-news.cfm/Article/INDUSTRY-NEWS/Urgent-Cybersecurity-Advisory-Nationwide-Cyberattacks-Targeting-Automatic-Tank-Gauges-ATGs/2026-4-14

In Food & Fuel. (2026, April 23). Cybersecurity alert: Automatic tank gauge systems targeted. https://www.infoodandfuel.org/news/cybersecurity-alert-automatic-tank-gauge-systems-targeted

PAS. (2025, April 24). Securing your Veeder-Root ATG: Protecting against vulnerabilities in remote connectivity. https://passtesting.com/news/securing-your-veeder-root-atg-protecting-against-vulnerabilities-in-remote-connectivity

Perplexity AI. (2026). Perplexity AI [Large language model]. https://www.perplexity.ai/

U.S. Environmental Protection Agency. (n.d.). Underground storage tanks (USTs). https://www.epa.gov/ust

Veeder-Root. (2024, August 14). Ensuring automatic tank gauge security compliance. https://www.veeder.com/us/ensuring-automatic-tank-gauge-security-compliance

AI Use Statement

Perplexity AI was employed in the research and development of this information. 

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Video: https://youtu.be/HbBIadarg60

AI: Prompts to Prevent AI Hallucinations

Dr. Frank Kardasz, MPA, Ed.D.

May 3, 2026

Here is a guide, ironically mostly AI generated, to prompts researchers can use to help prevent AI from misquoting or fabricating reference sources:

Why AI Misquotes Sources

AI language models generate text by predicting plausible patterns, not by retrieving verified facts. When asked for citations, they produce text that looks like legitimate academic references because they've seen similar patterns during training. This phenomenon — sometimes called "vibe citing" — affects an estimated 17–55% of AI-generated references. Prestigious conferences like NeurIPS 2025 have discovered over 100 hallucinated citations in accepted papers.^[1][2]

Category 1: Guardrail Prompts (Forbid Fabrication)

These prompts set hard rules before the AI generates any content:^[3]

·       The Non-Invention Constraint:

"You must not generate any citation, reference, or source that is not verifiable. If you cannot find a source for a specific claim, state: 'I could not find a verifiable source for this specific claim.' Never invent a source."

·       The Epistemic Accuracy System Prompt:

"You are a fact-conscious assistant. Your core principle is: 'If it is not verifiable, do not claim it.' Do not fabricate data, names, dates, events, studies, or quotes. Do not simulate sources or cite imaginary articles. When unsure, say: 'I don't know' or 'This cannot be confirmed.'"^[4]

·       The Boundary Constraint:

"Use only the sources I provide. If the answer isn't there, say: 'I could not find that in my knowledge sources.'"^[5]

Category 2: Source-Grounded Prompts (Anchor AI to Real Text)

The most reliable strategy is to paste the actual source text into the prompt, forcing the AI to work only from what you provide:^[6]

·       The Context-Lock Prompt:

"Generate a synthesis based ONLY on these papers: [paste full abstract or text]. Do NOT invent citations. Do NOT cite papers not in this list. Include exact quotes with page numbers."^[1]

·       The Verbatim Excerpt Prompt:

"Extract a verbatim excerpt — not a paraphrase — from the text I have pasted below that supports [claim]. If no direct excerpt supports this claim, say so explicitly."^[5]
(Note: Using the word "verbatim" and asking for an "excerpt" rather than a "quote" dramatically improves copy-paste accuracy, as "quote" tends to invite paraphrase.)^[5]

·       The RTCF Structured Citation Prompt (Role–Task–Context–Format):

"You are an academic citation specialist [Role]. Generate a complete APA 7th edition citation [Task] for the following source: [paste all known bibliographic details — author, year, title, journal, DOI] [Context]. Output a single reference entry in APA 7th edition format [Format]."^[6]

Category 3: Chain-of-Verification (CoVe) Prompts

This is a four-stage method developed by Meta researchers that forces the AI to self-check its own output independently before finalizing it:^[7][8]

1.      Stage 1 – Draft: Generate the initial claim or citation.

2.     Stage 2 – Plan verification questions: "List the specific questions you would need to answer to verify each claim you just made."

3.     Stage 3 – Answer independently: "Now answer each verification question independently, without referencing your earlier response."

4.     Stage 4 – Reconcile: "Compare your verification answers to your original draft. Correct any claims that are not fully supported. If a citation cannot be verified, remove it."

A condensed single-prompt version of CoVe is:^[3]

"First, generate the claim. Second, search your knowledge base for the supporting source. Third, compare the claim to the source. Fourth, only if verified, output the claim and citation. If unverified, omit."

Research confirms CoVe decreases hallucinations across list-based, closed-book, and long-form generation tasks.^[8]

Category 4: Cross-Model Fact-Check Prompts

A practical technique is to pipe one AI's output into a second AI for verification:^[9]

"Fact-check the following claim against its cited sources. For each source: (1) Confirm the URL is real and reachable; (2) Determine whether the source directly supports, contradicts, or is unrelated to the claim; (3) Spot any misrepresentation, selective quoting, or omitted context; (4) Give a verdict: well-supported, partially supported, unsupported, or contradicted."^[9]

You can also use a follow-up verification prompt directly with the same AI:^[6]

"For the citation you just gave me, is [Journal Name] a real peer-reviewed journal? What is its ISSN? Can you confirm that DOI [DOI number] leads to the article titled [Article Title]?"

Category 5: Structural Accountability Prompts

These prompts build traceability into the AI's output format:^[10][5]

·       Chunk-referencing prompt (useful when you provide a document):

"I have numbered my source text in chunks,, … For every claim you make, reference the chunk number you pulled it from in brackets."^[11][12][9]

·       Forced citation format prompt:

"Provide legal/factual statements ONLY with a citation in this format: [Author, Year, Title, DOI/URL, page number]. If you cannot supply all fields, do not include the claim."^[10]

·       Confidence-flagging prompt:

"For each claim, label it as: (A) Verified from provided text, (B) From general training knowledge — needs verification, or (C) Uncertain — do not use. Do not present (B) or (C) claims as established facts."^[11]

Quick-Reference Prompt Table

Goal	Prompt Keyword/Technique	Source
Prevent fabricated citations	"Never invent a source" + honesty instruction	[3]
Lock AI to provided text	Paste source text + "based ONLY on these papers"	[1]
Force verbatim quotes	Use "verbatim" + ask for "excerpt" not "quote"	[5]
Self-verification	Chain-of-Verification (CoVe) 4-step prompt	[8]
Cross-model checking	Pipe output to second AI with fact-check prompt	[9]
Structural traceability	Numbered chunks + bracket referencing	[5]
Confidence transparency	Label claims A/B/C by verification status	[11]
Citation format accuracy	RTCF method (Role, Task, Context, Format)	[6]

 

The Non-Negotiable Rule

No prompt fully eliminates the risk. Even with all techniques applied, manual verification against the original source remains mandatory. Tools like Elicit, Consensus, Scite.ai, and Zotero are specifically designed for scholarly citation retrieval and validation and should be used alongside AI writing tools. The architecturally safest approach is Retrieval-Augmented Generation (RAG), which reduces hallucination rates by up to 71% by forcing the AI to generate only from pre-verified, retrieved documents.^{[12][13][2][14][15][9][1]}

 

1.      https://www.inra.ai/blog/citation-accuracy   

2.     https://www.youtube.com/watch?v=YtdIjpL-kB8 

3.     https://westoahu.hawaii.edu/distancelearning/tips/stop-hallucinating-3-prompts-that-make-ai-a-reliable-partner/  

4.     https://www.linkedin.com/posts/how-to-prompt_a-system-prompt-to-reduce-ai-hallucination-activity-7327636143884099584-jfFv

5.     https://www.linkedin.com/posts/jamesbickerton_the-4-ai-prompts-that-finally-got-me-accurate-activity-7333484323947356162-mV_h     

6.     https://www.getpassionfruit.com/blog/blog-ai-prompt-engineering-citations   

7.     https://www.reddit.com/r/singularity/comments/16qcdsz/research_paper_meta_chainofverification_reduces/

8.     https://arxiv.org/abs/2309.11495  

9.     https://www.reddit.com/r/PromptEngineering/comments/1m368sn/how_do_you_get_an_ai_to_actually_use_and_cite/    

10.  https://aiforlawyers.substack.com/p/top-ten-ways-to-eliminate-or-reduce 

11.   https://www.aiprompthackers.com/p/8-copy-paste-ai-prompts-to-stop-hallucinations  

12.   https://library.up.ac.za/c.php?g=1509323&p=11285631 

13.   https://libguides.brown.edu/c.php?g=1338928&p=9868287

14.   https://www.itconvergence.com/blog/how-to-overcome-ai-hallucinations-using-retrieval-augmented-generation/

15.   https://www.linkedin.com/posts/clevia-ai_ghost-citations-are-becoming-a-real-research-activity-7432091216625766400-UwDg

16.   https://guides.lib.utexas.edu/AI/academic_integrity

17.   https://library.fiu.edu/reportingthenews/plagiarism

18.  https://www.pangram.com/blog/how-to-create-evidence-for-an-ai-detection-case

19.   https://lib.guides.umd.edu/c.php?g=1340355&p=9896961

20.  https://www.reddit.com/r/UniUK/comments/1hez1sj/how_can_universities_lecturers_tell_students_have/

21.   https://arxiv.org/abs/2404.08189

22.  https://arxiv.org/html/2509.05741v1

23.  https://guides.lib.usf.edu/AI/promptengineering

24.  https://arxiv.org/pdf/2403.01193.pdf

25.  https://www.reddit.com/r/PromptEngineering/comments/1oczlny/building_a_fact_checker_prompt/

26.  https://techcommunity.microsoft.com/blog/azure-ai-foundry-blog/best-practices-for-mitigating-hallucinations-in-large-language-models-llms/4403129

27.  https://arxiv.org/abs/2405.00204

28.  https://www.frontiersin.org/journals/artificial-intelligence/articles/10.3389/frai.2025.1658316/full

29.  https://aws.amazon.com/blogs/machine-learning/detect-hallucinations-for-rag-based-systems/

Public Safety: Officer Involved Shooting - “I only fired three rounds!?”

Introduction

Officer-involved shootings (OISs) are among the most scrutinized situations in policing, yet the officer’s own perception of what occurred is often incomplete or inaccurate, especially regarding the number of rounds fired. These discrepancies are frequently interpreted as evidence of deception, even though research shows they are a predictable consequence of neurophysiological stress responses, training artifacts, and trauma-related memory distortion.[1][2][3]

   
This article analyzes why an officer may state, “I only fired three rounds,” when forensic evidence establishes that many more rounds were discharged, and then explores implications for training, trauma, post-incident investigation, officer interrogation and counsel, legal ramifications, and defense strategies—including the use of case law and structured cross-examination both to challenge and to rehabilitate officer credibility.[4][2][5][1]

Perceptual and Memory Distortion in OISs

 

Neurophysiological Stress Responses and Round-Count Errors

Research documents that officers in shootings experience intense physiological arousal accompanied by perceptual and memory distortions. Artwohl’s survey of 157 officers found that 84% reported diminished sound (auditory exclusion), 79% reported tunnel vision, 62% experienced time slowing, and 52% reported memory loss for part of the event, with 46% unable to recall some of their own behavior. Klinger’s interviews in 113 OISs similarly revealed high rates of auditory blunting, narrowed attentional focus, and fragmented recall.[2][5][1] 

These distortions directly impair accurate round counting. Artwohl’s analysis of Klinger’s data found that 33% of officers could not accurately recall the number of rounds they fired, and that accuracy decreased sharply as the number of shots increased—from 81% accuracy with five or fewer rounds to 29% with six to nine rounds, and 0% when 13 or more rounds were fired. In other words, once a shooting escalates into a sustained volley, accurate self-report of round count becomes highly unlikely, even in lawful, objectively reasonable shootings.[1][2]

“No recall” and Partial Recall of Discharges

Case histories show that some officers fire their weapons yet have no conscious memory of doing so until confronted with physical or forensic evidence. Artwohl describes officers who:[1]

• Fired their service weapon, but only learned of it when magazine counts or ballistic evidence revealed discharges they did not recall.[1]
• Recalled only a subset of their shots and believed muzzle flashes they saw were from the suspect rather than from their own weapon.[1]
• Participated in high-stress training drills where 85–90% of officers exhibited memory gaps about whether they had fired at particular stations, despite clear physical evidence of shots.[1] 

These patterns support the position that an officer’s statement—“I think I fired three rounds”—is best understood as a stress-influenced estimate rather than a deliberate falsehood. The combination of auditory exclusion, attentional narrowing, automatic motor responses, and trauma-related encoding deficits makes misestimation of rounds both expectable and scientifically explicable.[2][1]

Training Influences on Count Misperception

 

Range Training Structure and “Low-Round” Schemas

Conventional firearms training tends to emphasize fixed, low round-count strings (for example, 2–3 rounds per drill) for ammunition conservation, time efficiency, and scoring simplicity. Officers become habituated to a schema in which handgun deployments are cognitively associated with small volleys of fire rather than sustained, threat-driven shooting.[3]

In many agencies: 

• Officers seldom fire all rounds in their weapon during a single drill; they fire a prescribed number, then holster or reload on command.[3]
• Drills occur at known distances, under predictable conditions, with explicit commands to “fire” and “cease fire,” creating a stable temporal structure unlike the chaotic onset and offset of real OISs.[2][3]
• Officers implicitly learn that “engaging a threat” typically means firing only a few shots, and that this pattern is normal and desired.[3]
• Officers do not practice reciting the number of rounds that they have fired after firearms training drills. 

When confronted with a real, rapidly evolving deadly-force encounter, the officer may fire until the threat stops, yet subsequent reconstruction of the event is filtered through the familiar, trained pattern of “a few rounds,” especially when memory is fragmented. Under stress, the brain fills gaps with plausible, training-based expectations; the result is a sincere but inaccurate estimate such as “two or three shots.”[2][3][1]

Controlled Conditions vs. Chaotic Reality

Standard live-fire range training differs from real shootings in several critical respects:

• Threat dynamics: Range drills rarely involve dynamic adversaries, realistic counterattacks, or complex movement, all of which increase cognitive load and reduce capacity for detailed self-monitoring.[3][1]
• Sensory environment: Officers train with ear and eye protection; in real incidents, ear protection is absent and eye protection is often not present, producing very different sensory inputs under extreme arousal.[2][1]
• Incident continuum: Training typically starts and ends at the firing line, omitting the full “arc” of an encounter from dispatch to resolution; officers therefore get limited rehearsal in sustaining situational awareness—including round count—across the entire incident.[3][1]

Stress-inoculation programs that attempt to simulate realistic threat levels (for example, force-on-force scenarios, complex “House of Horrors” drills) reveal that even in training, officers frequently misremember how many shots they fired or whether they fired at all. This indicates that performance under stress can be robust while contemporaneous self-monitoring remains imprecise.[2][1]

Traumatic Psychological Effects of Being Involved in a Shooting 

 

Acute and Subacute Reactions

Officer involved shootings are critical incidents and can trigger acute stress reactions and longer-term trauma responses. During the event, officers commonly experience:[5][3][2]

• Intense fear and survival-focused cognition (“I thought I was going to die”).[3]
• Perceptual distortions such as tunnel vision, auditory exclusion, and time slowing or speeding.[1][2]
• Dissociation or detachment, reported by roughly 39% of Artwohl’s sample, including feelings of unreality or watching the incident as if from outside their body.[2]

In the immediate aftermath, officers may exhibit nausea, headaches, shaking, emotional numbing, and difficulty sleeping. Solis’ study of officers in deadly-force encounters found that many reported intense concern about legal and administrative consequences, recurrent intrusive thoughts, fatigue, and sleep disruption in the weeks and months following the incident.[3]

Post-Shooting Trauma and Long-Term Outcomes

The concept of “post-shooting trauma” describes a cluster of PTSD-like symptoms as well as possible post-traumatic growth. Officers may experience:[3]

• Intrusive recollections and nightmares about the shooting.
• Avoidance of reminders, emotional numbing, irritability, and hypervigilance, sometimes accompanied by substance misuse or social withdrawal.[6][3]
• In some cases, positive changes such as increased appreciation of life or strengthened relationships, once they process the event with adequate support.[3]

These psychological consequenses can further affect memory. Over time, recall may become more coherent or, conversely, more distorted as officers re-narrate events in light of media coverage, legal proceedings, and internal ruminations. Investigators and courts must recognize that evolving statements can reflect trauma and memory reconstruction as much as intentional revision.[1][2][3]

Aftermath: Investigative Scrutiny and Officer Statements

Memory Limitations and Investigative Expectations

Investigators, prosecutors, and the public often expect officers to provide precise, linear narratives of shootings, including exact round counts and sequences. Yet cognitive science demonstrates that memory is reconstructive and vulnerable to fragmentation under stress; discrepancies between statements and physical evidence are not, by themselves, reliable indicators of deceit.[5][2][1]

 
Artwohl and others caution that officers who lack recall of all shots fired may be unfairly accused of lying or covering up, even when neurophysiological explanations are well-supported. Klinger’s findings that recall accuracy drops to 0% when 13 or more rounds are fired highlight the danger of equating misremembered round count with intentional falsehood. Investigators should integrate officer accounts with scene evidence, body-worn camera footage, and forensic analysis, viewing inconsistencies through the lens of stress-related memory distortion.[5][1][3]

Recommended Approaches to Officer Interviews

Several scholars and professional bodies recommend delaying detailed, formal interviews of involved officers for at least 24 hours to allow for physiological recovery and memory consolidation, while still obtaining immediate public-safety information. Cognitive Interview techniques—open-ended prompts, context reinstatement, and multiple retrieval attempts—can facilitate more complete and accurate recall without suggestive questioning.[5][2][1]

 
Investigators should be trained in the normalcy of perceptual distortions and memory gaps in OISs and should avoid implying that any discrepancy equals deception. Agency policies that explicitly acknowledge these phenomena can assist in later litigation, demonstrating that such inconsistencies were anticipated and not automatically treated as misconduct.[2][1][3]

Interrogation, Legal Counsel, and Officer Rights

Immediate Post-Incident Statements and the Right to Remain Silent

After a shooting, officers simultaneously function as key witnesses and potential criminal suspects. Best practices distinguish between narrowly tailored public-safety questions (for example, location of suspects, weapons, injured parties) and comprehensive criminal interrogation. Officers should provide necessary safety information but are generally advised to avoid detailed statements until they have consulted legal counsel.[7][5]

Many legal defense funds and professional associations recommend that officers:

• Provide identifying information and immediate safety-related details.
• Decline to give comprehensive narrative statements at the scene, especially when physically and emotionally compromised.
• Invoke their right to counsel before participating in formal criminal or administrative interviews.[7][5]

This approach is consistent with constitutional protections and recognizes that statements made under extreme stress may be inaccurate and later used for impeachment, even when not intentionally false.

Administrative vs. Criminal Interviews and Garrity Protections

In many jurisdictions, officers may be compelled to provide administrative statements under Garrity-type protections, which generally preclude use of those statements in criminal proceedings. However, voluntary criminal statements and informal comments at the scene are usually admissible. Agencies and unions should therefore ensure that officers understand:[7]

• The difference between compelled administrative interviews and voluntary criminal interviews.
• The importance of having counsel present for any interview that might implicate criminal liability.
• That casual remarks about round counts or sequence of shots may later be juxtaposed with forensic evidence to suggest dishonesty.

Careful coordination between administrative and criminal processes helps protect both the integrity of the investigation and the officer’s constitutional rights.[7][5]

Legal Ramifications of Misstated Round Counts

Objective Reasonableness and Multiple Shots

Fourth Amendment excessive-force analysis focuses on objective reasonableness, not on perfect recollection of every shot. In Plumhoff v. Rickard (2014), the U.S. Supreme Court held that officers did not violate the Fourth Amendment when they fired 15 shots to terminate a dangerous high-speed chase, emphasizing that reasonableness must be evaluated from the perspective of a reasonable officer on the scene and that multiple shots within a single rapidly evolving encounter do not transform an otherwise reasonable use of deadly force into a constitutional violation.[8][4]

Similarly, appellate courts have analyzed shootings involving multiple volleys by treating each volley as a distinct use of force, yet often extending qualified immunity where threats persisted and the time between volleys was short. In a Ninth Circuit decision summarized in 2024, an officer’s six shots were parsed into three separate uses of force, with the first two deemed reasonable as a matter of law and qualified immunity granted for the third volley as well, given the evolving threat and brief time intervals.[9]

Round count therefore matters, but primarily in relation to whether officers reassessed the threat as conditions changed; it is not, by itself, dispositive of reasonableness.

Misstatements, Credibility, and Impeachment

An officer who states at the scene, “I think I fired three rounds,” when forensic evidence later shows 10 or more discharges, risks impeachment in both criminal and civil proceedings. Prosecutors or plaintiffs’ counsel may argue that:

• The initial statement was an intentional minimization designed to conceal excessive force.
• The inconsistency reflects a broader unreliability in the officer’s account.
• The officer is willing to shade or distort facts to justify the shooting.

In civil rights litigation under 42 U.S.C. § 1983, such inconsistencies may be framed as evidence of “tailored” testimony, especially when combined with other discrepancies. Administrative bodies may likewise treat inaccurate statements about round count as potential dishonesty, leading to discipline or termination even where the shooting itself is deemed lawful.[10][11][12]

At the same time, because research strongly supports the normalcy of memory distortion under extreme stress, defense counsel can argue that misstatements about rounds reflect trauma rather than deceit, especially when immediately qualified as estimates (for example, “I think,” “I believe”).[1][2][3]

Case Law Touchpoints

Key cases that can inform training on multiple shots and officer recollection include:

• Plumhoff v. Rickard, 572 U.S. 765 (2014): Multiple rounds (15 shots) in a dangerous pursuit were held objectively reasonable, emphasizing that reasonableness is assessed in light of the entire encounter, not shot-by-shot in isolation.[4]
• Ninth Circuit multiple-volley case (2024 summary): Six shots analyzed as three uses of force; court granted qualified immunity where threat persisted and intervals were brief, illustrating that courts closely examine sequence and reassessment.[9]
• Other excessive-force decisions (for example, those addressing “moment of threat” analyses) demonstrate that courts increasingly scrutinize whether officers reassessed between volleys, but still accept that multiple shots in a rapidly evolving event can be reasonable.[13][14]

In training, these cases can be used to show that: (a) courts expect officers to reassess as circumstances change, and (b) multiple shots alone do not equate to excessive force, but inaccurate statements about shots can damage credibility.

Defending the Officer: Explaining Misstated Round Counts

Using Empirical Research and Expert Testimony

Defense attorneys should present peer‑reviewed research and professional literature to reframe round-count discrepancies as products of trauma and training, not moral failure. This includes: 

• Artwohl’s work on perceptual and memory distortions, documenting high rates of auditory exclusion, tunnel vision, and partial amnesia in OISs.[2][1]
• Data from Klinger showing declining recall accuracy as round counts increase, with 0% accuracy when 13 or more shots are fired.[1]
• Solis’ findings on post-shooting psychological effects, showing that fear, intrusive recollections, and sleep disruption can affect recall and reporting.[3]

Expert witnesses in police psychology, human factors, and use of force can explain to jurors that misestimating round count is consistent with well-established stress responses and does not indicate dishonesty.[2][1][3]

Connecting Training Practices to Expectation Errors

Defense counsel should also explore the officer’s firearms training, emphasizing:

• Standard use of fixed, low round-count drills that reinforce a cognitive expectation of firing just a few rounds per engagement.[3]
• Limited exposure to high-stress, high-volume engagements that integrate realistic threat dynamics and require ongoing reassessment.[1][3]
•  Absence of training that teaches officers to monitor exact round count under life-threatening stress, making such precision an unrealistic expectation.[1][3]

By situating the misstatement within institutional training practices, counsel can argue that the discrepancy reflects systemic training limitations rather than individual deceit.

Emphasizing Consistency on Core Facts

Effective defense strategy focuses on showing that, despite misestimation of rounds, the officer’s core narrative of the threat and justification for force remained consistent and is corroborated by independent evidence. Counsel can highlight that:

• The officer consistently described the suspect’s threatening behavior (for example, pointing a firearm, charging with a weapon).
• Physical and video evidence substantively support this description.
• The only inconsistency concerns a detail—exact round count—that research shows is highly vulnerable to stress-related distortion.[5][2][1]

This approach aligns with Plumhoff and similar cases, where courts assess reasonableness based on the totality of circumstances rather than on perfect recollection of every shot.[4]

Example Cross‑Examination Questions for Training

The following examples are designed for use in academy and in‑service training to illustrate how prosecutors or plaintiffs’ attorneys might attack an officer’s credibility over miscounted rounds—and how defense counsel and experts might respond. 

Prosecution/Plaintiff-Style Cross-Examination (officer witness)

Theme: Prior Inconsistent Statement and Minimization of Force

1. “Officer, at the scene, you told investigators, ‘I think I fired three rounds,’ correct?”
2. “You knew at that time that a man had been shot multiple times and was in critical condition, did you not?”
3. “You now agree that you actually fired 11 round, correct?”
4. “That is more than three times what you told investigators at the scene, isn’t it?”
5. “When you spoke with investigators, you understood the seriousness of the situation, correct?”
6. “You had been trained for years to document your use of force accurately, true?”
7. “Yet in this most critical incident of your career, you understated your use of force by eight shots, didn’t you?”
8. “You did not say, ‘I don’t know how many rounds I fired,’ did you? You gave a specific estimate—three rounds.”
9. “You also did not tell them that your memory might be impaired or that you felt disoriented, correct?”
10. “Officer, isn’t it fair to say that by reporting only ‘three rounds,’ you made this shooting appear less severe than it actually was?”

Training discussion: Trainees can analyze how each question narrows the officer’s options, builds a theme of minimization, and uses ordinary expectations about memory to imply dishonesty. Trainers can then introduce the research on perceptual and memory distortions to discuss how an officer might honestly respond while acknowledging uncertainty.

Defense-Style Cross-Examination Rehabilitation (officer witness)

Theme: Stress, Trauma, and Honest Estimation Under Uncertainty

1. “Officer, when you said, ‘I think I fired three rounds,’ did you intend to lie to investigators?”
2. “At that moment, you had just been involved in a life‑threatening encounter where you believed you might be killed, correct?”
3. “You were shaking, your heart was racing, and you were experiencing intense stress, right?”
4. “You used the phrase, ‘I think,’ to indicate that you were estimating, not stating a precise number, correct?”
5. “You also told investigators that everything happened very fast and that some details were unclear to you, didn’t you?”
6. “You had never before in your career fired your weapon at a person, correct?”
7. “You were aware that, under stress, officers can experience auditory exclusion and memory gaps, something you had been taught in training, correct?”
8. “After you had time to recover physically and review the investigative findings, you acknowledged that you fired more rounds than you initially estimated, correct?”
9. “You did not attempt to change the physical evidence, or the videos, or the cartridge casings, did you?”
10. “So today, your testimony is that your initial statement reflected an honest but mistaken estimate under extreme stress, not an attempt to mislead anyone, correct?”

Training discussion: Trainees can examine how these questions allow the officer to explain the context of the misstatement and emphasize honesty, while aligning their testimony with known phenomena like auditory exclusion and memory distortion.[2][1]

Expert Witness Cross-Examination (Memory/Psychology Expert)

Prosecution/Plaintiff-Style Questions

1. “Doctor, you would agree that police officers are trained to accurately document their uses of force, correct?”
2. “You did not personally examine the officer in this case at the time of the shooting, did you?”
3. “Your opinion that his misstatement about the number of rounds was caused by ‘stress’ is based on general research, not on any direct measurement of his brain function, correct?”
4. “You cannot say, to a reasonable degree of scientific certainty, that this officer could not have accurately counted his own shots, can you?”
5. “In fact, many people involved in critical incidents do accurately recall important details, do they not?”
6. “Isn’t it true that your field cannot distinguish a genuine memory gap from a convenient ‘I don’t remember’ with certainty?”

Defense-Style Questions

1. “Doctor, are perceptual and memory distortions during officer‑involved shootings widely documented in the literature?”[2][1]
2. “Does research show that as the number of rounds fired increases, officers’ recall of that number becomes less accurate?”[1]
3. “In the studies you reviewed, have some officers completely failed to recall firing shots that physical evidence later confirmed?”[1]
4. “Do these findings indicate that an officer who misestimates the number of rounds fired may nonetheless be telling the truth as he or she remembers it?”[2][1]
5. “Would you agree that expecting precise round counts from officers in life‑threatening encounters can be inconsistent with what we know about human memory under extreme stress?”[2][1]