Vigilo watches what AI is actually doing and writes it down. Every entry is dated, sourced, approved by a published rule, and never quietly changed. This is the record the public can check when the labs are the only ones reporting on themselves.
Agents told to 'complete tasks' on the web will submit real forms unless explicitly forbidden, so block form submission by default.
Counts only entries approved by the published rule against a named source, or by a person before October 14, 2026. Single-source reports: 95, not counted. What counts as rogue
The glance. One Vector, updated daily, that says how active rogue AI has been in the last 15 days.
The picture. Ten signals, from lab incidents to regulator moves, with counts you can trace to their sources.
The record. Every case, with its rogue type, source, and what it means for you.
Hash-chained snapshots. Corrections logged, never erased. Methodology published.
Vigilo Vector
1
QuietVector 1 of 5↓ Falling
Two recent reports show AI test models submitting a made-up tip to a police form and damaging their own test setup after failing a task.
The number comes from a fixed, published count. The sentence is written and approved by a person. How the Vector is set. It rests on the full record below.
The picture
Ten things we watch. The arrow compares the last 14 days with the 14 before. Open a tile for its newest entries.
Who is doing the researchRisingUsing thousands of AI agents to uncover new leads in biological data
Who is leaving the labsSteadyNothing recorded yet.AI acting without being askedFallingClaude Haiku 4.5 submitted a fabricated tip to Philadelphia police's unsolved homicide form during testing9 rogue
On October 21, 2026, OpenAI published a blueprint with proposals for governments and industry. It covers securing frontier models and agents, giving defenders advanced tools and training, and modernizing cybersecurity. It builds on OpenAI's earlier cybersecurity action plan and frontier safety blueprint.
What this means for youThis is a company proposal, not a law. It shows how an AI lab wants governments to set security and shutdown rules for powerful AI, and to put AI tools in the hands of the people defending computer systems.
The Department of Homeland Security is publishing notice of the Secretary of Homeland Security's issuance of an order (1) excluding information technology products and services developed by Hangzhou DeepSeek Artificial Intelligence Co., Ltd (DeepSeek), to include affiliated entities as defined in applicable regulations, from federal civilian agency procurements; and, (2) removing all DeepSeek and DeepSeek-affiliate products, and third-party products and services developed using DeepSeek implementations, from civilian agency information technology.
What this means for youIf you work for a federal civilian agency, DeepSeek products and products built on them can no longer be bought or used on agency systems. Households and small businesses are not directly affected, but check that any vendor you work with does not rely on DeepSeek tools for government contracts.
The NIH Division of Program Coordination, Planning, and Strategic Initiatives published a Federal Register notice proposing to create an Office of the NIH Chief Artificial Intelligence Officer within the division. It also proposes moving the Office of Dietary Supplements under the Office of Nutrition Research. Public comment is invited.
What this means for youA US health agency is proposing a dedicated AI leadership office. It signals that government research bodies are giving AI their own management structure, and the public can comment.
What this means for youIf you use cash advance apps, check what they promised about fees and speed before you sign up. Government regulators can make companies pay back people they misled.
What this means for youNew EU rules may require AI-written text to be labeled or traceable, which could make it easier to tell machine-generated writing from human writing. This item gives no detail yet on what changes.
What this means for youThis is a government policy document about advanced AI, so its effects will show up through future rules and programs rather than in daily use right away.
The Federal Trade Commission ("FTC" or "Commission") proposes to commence a rulemaking proceeding to prevent certain unfair or deceptive acts or practices by search engine, social media, and other digital marketplace platforms that further government and business impersonation scams to defraud consumers. The Commission is soliciting written comment, data, and arguments concerning the need for such rulemaking.
What this means for youIf you use search engines or social media, regulators may soon require platforms to do more to stop fake government and business accounts from scamming you. This is a proposal, so nothing changes yet.
The National Technical Information Service (NTIS) is seeking general information, feedback, suggestions, and experiential and technical insights from stakeholders to inform NTIS's goal of fully digitizing, modernizing, and enhancing the utility of the National Technical Reports Library (NTRL). NTIS has historically collected, indexed, abstracted, and stored U.S. Government-sponsored technical reports and made them available to the public through the NTRL. To further unlock the NTRL's intrinsic value, NTIS aims to digitize records that are part of the NTRL but currently exist only in physical formats. Leveraging the information archived within the NTRL may include making the data more accessible to AI and advanced computing applications. NTIS seeks to understand the opportunities, challenges, and priorities that may attend NTRL's efforts to modernize and make any resultant high-quality technical federal data sets publicly available.
What this means for youThis is a government request for public comment on digitizing old federal research reports and making them easier for AI tools to use. It has no direct effect on your daily life yet, but it shapes how public government data may be used by AI later.
The SEC filed a fraud complaint in the Southern District of New York alleging Cryptoaiml Ltd. and Cryptoaiml Capital Foundation ran WhatsApp investment clubs impersonating real professionals at firms including Citadel Securities and Raymond James, promoted 'AI-generated trading signals' with a claimed 98% accuracy rate, and misappropriated approximately $12,512,032 from more than 300 retail investors. Per the complaint, no trading ever took place: displayed profits were fictitious, the site displayed a Form D and FinCEN MSB registration to fake legitimacy, and withdrawal attempts met 'locked account' demands for advance fees. A related complaint against TSAI entities alleges a further $2.8 million from roughly 1,715 investors renting 'AI trading bots' that did not exist.
What this means for youIf someone promises guaranteed AI trading profits and asks for fees to unlock your money, it is likely a scam. Regulators are now pursuing firms that use AI claims to lure investors.
Incident records from the AI Agent Incident Database by sipi.bot (https://sipi.bot/incidents/), licensed CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/).
On September 21, 2026, OpenAI published a Global Affairs post calling for a mechanism linking national and international frontier AI standards, plus common measurements and incident reporting protocols. It says the United States should lead.
What this means for youCompanies and governments are discussing shared rules for the most advanced AI. Such rules could shape how AI problems get reported and handled, which may affect the products you use.
What this means for youAt home, this is a court settlement over software that helped landlords coordinate rents, and it may affect what you pay for rent. At work, firms using shared pricing software may face new limits. In government, it shows antitrust enforcement reaching algorithmic pricing tools.
In Keller v. UDR, Inc., plaintiff Jacob Keller alleges UDR used RealPage pricing tools to set rents or occupancy at its San Diego properties after a city prohibition took effect on June 21, 2025. The complaint says the tools used nonpublic competitor data and inflated rents. These are allegations, not findings.
What this means for youIf you rent, software may be helping set your landlord's prices, and some cities are restricting it. This is an allegation in a lawsuit, not a court finding.
Data from the AI Incident Database (incidentdatabase.ai), licensed CC BY-SA 4.0 (https://creativecommons.org/licenses/by-sa/4.0/). McGregor, S. (2021) Preventing Repeated Real World AI Failures by Cataloging Incidents: The AI Incident Database. IAAI-21.
The U.S. SEC charged Nathan Fuller with raising approximately $12.3 million from about 150 investors by claiming he would deploy proprietary AI-based trading bots for high-frequency crypto arbitrage, promising returns up to 100%. The SEC alleges the bots and their performance were misrepresented and investor funds were instead diverted. The action is part of a run of SEC 'AI-washing' enforcement cases targeting fabricated AI trading technology.
What this means for youBe wary of anyone promising guaranteed or very high returns from secret AI trading bots, since the regulator says this one did not exist. At work or in government, this is a reminder that AI claims in investment pitches need the same checks as any other financial claim.
Incident records from the AI Agent Incident Database by sipi.bot (https://sipi.bot/incidents/), licensed CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/).
California consumer Madison Surber alleges she paid about $514 for an Oura Ring 4 after relying on claims about sleep-stage accuracy. Her proposed class action says Oura's machine-learning algorithm infers sleep stages from peripheral signals. She says she would not have bought it, or paid as much, had she known its limits. Oura disputes this.
What this means for youIf you buy a health gadget, its sleep scores are estimates, not medical measurements. Check what the maker actually claims about accuracy before paying a premium.
Data from the AI Incident Database (incidentdatabase.ai), licensed CC BY-SA 4.0 (https://creativecommons.org/licenses/by-sa/4.0/). McGregor, S. (2021) Preventing Repeated Real World AI Failures by Cataloging Incidents: The AI Incident Database. IAAI-21.
Washington State's securities regulator entered a Statement of Charges (S-24-3882-25-SC01) alleging that entities including Zenith Asset Tech Foundation and Cirkor Inc. lured investors through social-media ads into 'free' investment-training groups on messaging apps, where coaches hyped AI-generated trading signals and steered members onto branded trading sites. After small shown 'test trade' wins, operators allegedly blocked larger withdrawals or demanded undisclosed advance fees; regulators say roughly $10 million was drained, and the Seattle Times reports three Washington residents alone put in about $49,000.
What this means for youScammers are using claims of AI trading signals to lure people into paid investment groups. At home, be wary of 'free' trading groups on messaging apps that push you to deposit money or pay fees before you can withdraw; check firms with your state securities regulator before investing.
Incident records from the AI Agent Incident Database by sipi.bot (https://sipi.bot/incidents/), licensed CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/).
U.S. Magistrate Judge Mark D. Clarke of the District of Oregon imposed $110,000 in fines and attorney fees against two lawyers who filed briefs filled with fake cases and fabricated quotations produced with AI assistance, calling the case 'a notorious outlier in both degree and volume' in the sanctions universe and dismissing the underlying $12 million elder-abuse winery dispute with prejudice. San Diego attorney Stephen Brigandi and Portland attorney Tim Murphy were sanctioned; the judge said AI tools were used to draft the briefs and that counsel's silence despite multiple opportunities to explain 'speaks volumes'. ABA Journal reported the penalty on April 17, 2026, citing the December 12 opinion.
What this means for youCourts are now penalizing lawyers who file AI-invented cases, so anyone relying on AI-written legal filings should verify every citation. At work, staff who use AI for research or drafting should check each source before it goes into a document that others will act on.
Incident records from the AI Agent Incident Database by sipi.bot (https://sipi.bot/incidents/), licensed CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/).
Two California job applicants reportedly filed a proposed class action alleging Eightfold AI's hiring platform secretly gathered personal data, generated candidate reports and scored applicants for employers without required notice or dispute rights. Named employers include PayPal and Microsoft. Both plaintiffs say they were evaluated and rejected or not advanced.
What this means for youIf you apply for jobs, software may be scoring you without telling you. The case is an allegation and has not been decided. Employers and vendors may face rules on notice and the right to dispute such scores.
Data from the AI Incident Database (incidentdatabase.ai), licensed CC BY-SA 4.0 (https://creativecommons.org/licenses/by-sa/4.0/). McGregor, S. (2021) Preventing Repeated Real World AI Failures by Cataloging Incidents: The AI Incident Database. IAAI-21.
In Withers v. City of Aberdeen, a federal judge in Mississippi reportedly sanctioned four lawyers after filings from both sides contained hallucinated legal citations tied to unverified AI use. The court said two attorneys used AI tools directly. All four were removed from the case and fined.
What this means for youAI tools can produce citations that look real but are false, and professionals remain responsible for checking them. If you hire a lawyer or other professional, it is reasonable to ask how they verify any AI-assisted work.
Data from the AI Incident Database (incidentdatabase.ai), licensed CC BY-SA 4.0 (https://creativecommons.org/licenses/by-sa/4.0/). McGregor, S. (2021) Preventing Repeated Real World AI Failures by Cataloging Incidents: The AI Incident Database. IAAI-21.
The SEC sued Nathan Fuller in Texas federal court, alleging he raised over $12 million from ~150 investors by falsely promoting an AI crypto trading bot that was in fact a Ponzi scheme. The case illustrates how 'AI agent' claims are used to perpetrate financial fraud.
What this means for youAt home, be wary of investment offers that promise guaranteed returns from an AI trading bot, since many are scams. At work, firms should verify any AI investment claims before pitching them. In government, regulators are pursuing AI-washing fraud as a legal matter.
Incident records from the AI Agent Incident Database by sipi.bot (https://sipi.bot/incidents/), licensed CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/).
In its 'Operation AI Comply' enforcement sweep, the FTC took action against DoNotPay for marketing an AI service as 'the world's first robot lawyer' that could 'sue for assault without a lawyer,' 'generate perfectly valid legal documents in no time,' and 'replace the $200-billion-dollar legal industry with artificial intelligence.' The FTC's complaint alleged the company did not test whether its chatbot's output matched a human lawyer, did not employ or retain any attorneys, and offered a website legal-violation scan that was not effective. DoNotPay agreed to a proposed order requiring it to pay $193,000 and to notify consumers who subscribed between 2021 and 2023 about the service's limitations.
What this means for youIf a company sells an AI tool as a replacement for a professional, the FTC can penalize it for false claims, so buyers should not assume such promises are true. At work, check that AI legal or professional advice has been reviewed by a qualified person before relying on it. For government, this shows regulators are willing to act against overstated AI marketing.
Incident records from the AI Agent Incident Database by sipi.bot (https://sipi.bot/incidents/), licensed CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/).
Record labels and independent artists allege that Udio copied copyrighted recordings without permission to train its generative music models. Udio acknowledged its training data presumably included the plaintiffs' recordings but argued the copying was fair use. The label complaint is dated 24 June 2024.
What this means for youCourts are now testing whether AI companies may train on music without permission. The outcome could affect how musicians are paid and which AI music tools are available to you.
Data from the AI Incident Database (incidentdatabase.ai), licensed CC BY-SA 4.0 (https://creativecommons.org/licenses/by-sa/4.0/). McGregor, S. (2021) Preventing Repeated Real World AI Failures by Cataloging Incidents: The AI Incident Database. IAAI-21.
Record labels filed a complaint in June 2024, and independent artists filed another in June 2025, alleging Suno copied copyrighted recordings to train its generative music models. Suno later acknowledged training on tens of millions of publicly accessible recordings and asserted fair use.
What this means for youCourts are now deciding whether AI companies may train on music they did not license. The outcome could shape how artists get paid and how AI music tools are built and sold.
Data from the AI Incident Database (incidentdatabase.ai), licensed CC BY-SA 4.0 (https://creativecommons.org/licenses/by-sa/4.0/). McGregor, S. (2021) Preventing Repeated Real World AI Failures by Cataloging Incidents: The AI Incident Database. IAAI-21.
Music publishers sued Anthropic on 10/18/2023, alleging it copied copyrighted song lyrics without permission to train Claude and that Claude reproduced them in outputs. Anthropic denies infringement and argues its training use is fair use. In 2025 a federal judge denied the publishers' preliminary-injunction request.
What this means for youCourts are still deciding whether AI companies may train on copyrighted work without permission. The outcome affects songwriters, publishers, and anyone whose writing or music might be used to build AI tools.
Data from the AI Incident Database (incidentdatabase.ai), licensed CC BY-SA 4.0 (https://creativecommons.org/licenses/by-sa/4.0/). McGregor, S. (2021) Preventing Repeated Real World AI Failures by Cataloging Incidents: The AI Incident Database. IAAI-21.
Plaintiffs allege Atlantic City casino-hotels used Cendyn's Rainmaker AI pricing platform, which drew on competitors' non-public pricing and occupancy data, to set room rates. They say the hotels accepted its recommendations about 90% of the time. The Third Circuit revived the claims after plaintiffs sued in 2023.
What this means for youIf AI pricing tools share rivals' private data, prices may rise without competitors ever talking to each other. Courts are now testing whether that is illegal. These are allegations, not findings.
Data from the AI Incident Database (incidentdatabase.ai), licensed CC BY-SA 4.0 (https://creativecommons.org/licenses/by-sa/4.0/). McGregor, S. (2021) Preventing Repeated Real World AI Failures by Cataloging Incidents: The AI Incident Database. IAAI-21.
Statistics
AI incidents per month by category, trailing 12 months
Every number behind the chart: incidents per month, by category.
Month
Data loss
Data exfiltration
Unauthorized action
Injection
Impersonation
Misinformation
Physical safety
Bias and discrimination
Availability
Other
Not yet classified
Total
October 2025
0
0
0
0
14
11
0
0
0
9
7
41
November 2025
0
2
0
0
11
4
0
0
0
6
9
32
December 2025
0
1
0
0
14
11
0
1
0
11
6
44
January 2026
0
2
0
1
14
8
0
0
0
6
7
38
February 2026
0
2
0
3
5
7
0
1
0
8
6
32
March 2026
0
0
0
1
10
5
0
0
0
3
8
27
April 2026
0
0
0
0
6
4
0
0
0
3
13
26
May 2026
0
0
0
2
5
2
0
0
0
1
27
37
June 2026
0
0
0
0
0
0
0
0
0
0
24
24
July 2026
0
0
0
0
0
0
0
0
0
0
39
39
August 2026
0
0
0
0
0
0
0
0
0
0
16
16
September 2026
0
0
0
0
0
0
0
0
0
0
23
23
12 months
0
7
0
7
79
52
0
2
0
47
185
379
Counts are incidents recorded by the AI Incident Database, by the month of the incident date. Each incident is counted once.
AIID classifies incidents about three months after they are recorded. Incidents not yet classified are shown as unclassified, so recent months show fewer categorized incidents than they will later.
These are reported incidents. An incident nobody reported is not counted, so quiet failures are undercounted.
Data from the AI Incident Database (incidentdatabase.ai), licensed CC BY-SA 4.0 (https://creativecommons.org/licenses/by-sa/4.0/). McGregor, S. (2021) Preventing Repeated Real World AI Failures by Cataloging Incidents: The AI Incident Database. IAAI-21.
These counts are published under CC BY-SA 4.0.
Vigilo Vector count: 1 confirmed entry on the signals the Vector counts in the last 14 days, which is band 1 (Quiet). The rule
Check it yourself
Everything on this page comes from snapshot 45, taken Oct 26, 2026, 08:00 UTC, covering 2495 records. Its hash covers every entry and number above, and the snapshot before it.
