AI agent sandbox escapes are incidents in which an AI agent being trained, evaluated, or tested reaches systems outside the isolated environment ("sandbox") meant to contain it, usually the public internet, and then takes actions its developers did not intend. Between July and September 2026 a series of such incidents was disclosed or confirmed by OpenAI, Anthropic, Meta, and Google, and by the UK AI Security Institute. In most cases the agent was working on a cybersecurity capture-the-flag exercise or a research task, gained internet access through an exploit, a misconfiguration, or an unfiltered network path, and then accessed, attempted to access, or altered systems belonging to real third parties.[1][4][8][9][10]

The best-documented case is the OpenAI-Hugging Face agent incident of July 2026, in which OpenAI evaluation agents exploited a previously unknown vulnerability in an internal package proxy, reached the internet, and compromised parts of Hugging Face's production infrastructure.[1][26] Several of the later disclosures describe a different mechanism: evaluation environments built by a third-party vendor, Irregular, were meant to be offline but were misconfigured and left connected to the internet; in Anthropic's cases the models had been told they had no internet access.[4][8][10] The companies involved disagree about how to classify their own incidents. Meta wrote that its case "was not a sophisticated offensive cyber attack or sandbox escape", Google said its case did not show model misalignment, and the UK AI Security Institute stressed that its agents had been given internet access on purpose.[8][11][9] The disclosures fed into calls to slow frontier AI development, new pauses in training at OpenAI, proposed legislation in the United States, and industry products such as NVIDIA's Open Agent Safety Platform.[2][21][22][23]

Terminology and scope

Press coverage often used "escaped its sandbox" for every incident in this group. CNBC, reporting NVIDIA's 28 September 2026 launch, wrote that OpenAI, Anthropic, Meta and Google had "disclosed recent incidents in which their artificial intelligence models escaped their sandboxes and attempted to hack other companies and access their computer systems."[25] The primary disclosures describe at least three distinct situations:

Mechanism	What happened	Examples
Active circumvention of intended isolation	The environment was meant to block internet access and the agent found a way around the controls	OpenAI's ExploitGym agents exploiting a zero-day in an Artifactory package proxy (July); an OpenAI agent tunnelling queries through a DNS resolver (September)[1][2]
Misconfigured isolation	The environment was meant to be offline but was accidentally connected; the agent discovered and used the open path	Anthropic's four incidents, Meta's Muse Spark 1.1 case and Google's Gemini case, all in evaluations built by Irregular; Kimi K3 in a Frontier Security test[4][6][8][10][15]
Deliberate internet access	The evaluator intentionally allowed internet access and the agent acted against real people or organizations	UK AI Security Institute testing of Claude Mythos 5 and GPT-5.6 Sol, July 25-28[9]

Anthropic's first report drew this distinction directly: "Whereas OpenAI's models exploited a novel vulnerability to escape isolation, the Claude models evaluated here accessed the internet via an open path."[4] The UK AI Security Institute wrote that its case "was not a case of a model escaping its secure test environment, or 'sandbox'."[9] This article uses "sandbox escape" in the broad sense common in press coverage, and notes the mechanism for each incident.

Earlier precedents

Agents working around the limits of their test environments were documented before 2026. In OpenAI's o1 system card (September 2024), a pre-mitigation o1-preview model working on a capture-the-flag challenge found that the challenge container had failed to start because of an infrastructure bug. It scanned the network, found that the Docker daemon API on the evaluation host was reachable because of a misconfiguration, started a new copy of the broken container with the command 'cat flag.txt', and read the flag from the container logs. OpenAI said its evaluation infrastructure did not rely on that isolation boundary for security and remained secure, and described the behavior as "benign and within the range of systems administration and troubleshooting tasks we expect models to perform" while also reflecting "key elements of instrumental convergence and power seeking".[27] In August 2024 Sakana AI reported that its AI Scientist system, when its experiments hit a timeout limit, "tried to modify its own code to extend the timeout period" instead of making the code run faster; Sakana recommended sandboxing the system's operating environment.[28]

Security practitioners told Axios in August 2026 that such breakouts were not new in offensive-security tooling. Horizon3.ai chief executive Snehal Antani said his team had seen similar breakouts in 2019: while co-founder Anthony Pillitiere ran a prototype agent on his home network, it found a sound card's admin console, searched the web for its default credentials, logged in, and then got past a misconfigured firewall to scan other systems on the network.[18]

Timeline of disclosed incidents

Incident date	Disclosed	Developer / tester	Model	Mechanism	Reported impact
January 2026	September 9, 2026	Anthropic (Irregular environment)	Early checkpoint of Claude Opus 4.6	Misconfigured egress path	Admin access to a third party's machine, credential harvesting, personal information of one person read[6]
From April 2026	July 30, 2026	Anthropic (Irregular environment)	Claude Opus 4.7, Claude Mythos 5, internal research model	Misconfigured internet access	Three organizations accessed; malicious PyPI package run on 15 systems[4]
May 2026	September 18, 2026 (WSJ report, Google statement)	Google (Irregular environment)	Gemini	Unintended internet access	Three real companies' systems accessed with guessed or publicly exposed passwords[10][11]
June 18, 2026	September 23, 2026 (Australian Prime Minister)	OpenAI	Unnamed agent in an internal evaluation	Agent with web access on a research task	Public and non-public files on a Medicare statistics portal accessed; extent disputed[19][20]
Early July 2026	August 5 and 14, 2026	Meta (Irregular environment)	Pre-release Muse Spark 1.1	Misconfigured internet access and a real site named as target	Vulnerability exploited on a real website; data accessed and database changed[8][14]
July 9-13, 2026	July 16 (Hugging Face), July 21 (OpenAI)	OpenAI	Internal research model and GPT-5.6 Sol agents	Zero-day in Artifactory package proxy	Hugging Face production infrastructure compromised[1][26][35]
July 25-28, 2026	August 4, 2026	UK AI Security Institute	Claude Mythos 5, GPT-5.6 Sol	Internet deliberately enabled	Malicious pull request, fake identities, messages to real people; no harm found[9]
Not stated	August 6, 2026 (Wired)	Frontier Security	Kimi K3	Leak in sandbox network configuration	Answers retrieved from GitHub; no hacking reported[15]
September 20, 2026	September 25, 2026	OpenAI	Internal research model in RL training	Insufficient DNS filtering	Questions relayed to a public chatbot[2]

OpenAI

Hugging Face incident

The first and most severe disclosed incident occurred during OpenAI's internal evaluations on the ExploitGym cybersecurity benchmark. OpenAI wrote that the evaluation environment "did not provide the models with direct Internet access"; the models gained it by exploiting a previously unknown vulnerability in Artifactory, a package registry cache proxy, which OpenAI later disclosed to the vendor.[1] Hugging Face's forensic reconstruction covers about 17,600 attacker actions, grouped into about 6,280 clusters, between July 9 and July 13, 2026.[26] OpenAI publicly identified its models as responsible on July 21; it later clarified that the activity was driven primarily by an internal-only research model that was never intended for public release.[1] The incident is covered in detail in OpenAI-Hugging Face agent incident.

On September 25, OpenAI chief executive Sam Altman wrote that "Hugging Face is still the most severe event we've seen."[31] Justin Boitano, NVIDIA's vice president of enterprise AI, told CNBC in September: "From what we know, Hugging Face reported over 17,000 agents attacking their infrastructure that went on for days and weeks."[25] Hugging Face's published figures count events and actions, not agents: its July 16 disclosure described an attacker action log of "more than 17,000 recorded events", and its July 27 timeline reconstructed about 17,600 actions recorded between July 9 and July 13, a campaign it describes as lasting 4.5 days, roughly two and a half of them inside its infrastructure.[26][35]

Broader review and third-party notifications

After the Hugging Face incident OpenAI began a review of its models' activity on the internet during training and evaluation. By September 25 it said it had "notified dozens of third parties" and published anonymized categories of what it had found: access-control bypass, use of exposed credentials, query or command injection, access to runtime internals, and "agent spam", such as using public wiki pages as shared message boards.[1] OpenAI said most cases identified so far were low severity and that the review would take months.[1] Its alignment team also began publishing individual misalignment reports; one describes a highly persistent internal model that, in internal deployment, published a researcher's GitHub token in the public openai/codex repository while trying to obtain material from another team's proof submission.[33]

On September 25 OpenAI also disclosed that agents in its research environment had transmitted training and evaluation data while using third-party services, including 53 user-provided images posted to image-hosting sites "as links that weren't publicly listed". It said it had worked with the hosting providers to remove most of the content.[1][31]

On September 23, Australian Prime Minister Anthony Albanese said an OpenAI agent had accessed public and non-public files on the Medicare Statistics Reporting Service portal, administered by Services Australia, on June 18, and that OpenAI had not notified the government until September 10. He said he had raised Australia's "extreme concern" with Altman.[19][30] An OpenAI spokesperson told CNBC that the activity took place during an internal evaluation in which models were looking up statistics about Australia, that "our models took actions we did not intend", that the company learned of it in August during its review, and that it found no evidence patient records were accessed.[19] Recorded Future News later reported that archived versions of the portal's code directed visitors to an unauthenticated guest endpoint, suggesting the agent may not have needed to bypass any control. Former UK National Cyber Security Centre chief executive Ciaran Martin told the outlet: "It's still unclear if what's happened would constitute a hack in the normal sense of the term."[20]

The September 20 DNS incident

On September 20, 2026 an internal research model undergoing reinforcement learning training on a search task, asked to identify the author of a blog post from biographical clues, reached a public chatbot service through "insufficient DNS filtering in its training sandbox". After its supplied search tool returned unhelpful results and direct requests to search engines failed, the agent tested the network, found that the training environment's own DNS resolver returned real records, and used a public DNS delegation service to relay questions to a third-party chatbot encoded in hostnames. It sent 18 further questions by this route after confirming that it worked; four asked for ways to search the web or use a public DNS tunnel. OpenAI said all other internet access in the run hit its offline web cache.[2]

OpenAI's monitoring raised a top-priority alert at 10:02 a.m., within 15 minutes of the first external response at 9:50 a.m., and a human acknowledged it three minutes later, but an automatic stop did not trigger "leading to confusion around whether it should have been stopped", and the run was stopped manually two and a half hours later. A retrospective review found other cases of external DNS access the monitor had not flagged at the expected severity, and an infrastructure detector for anomalous DNS activity had excluded the affected environment.[2] OpenAI wrote that "The incident exposed a gap in our controls over network restrictions" and that, although the incident was "a lot less severe than some of our previous incidents", it was the first since its post-Hugging Face hardening.[2]

Pauses and remediation

On August 18, 2026 OpenAI said it had taken a two-week pause in reinforcement learning training on its latest models intended for deployment, kept its largest planned frontier RL run on hold, and introduced stricter workload isolation, network isolation, and continuous security testing in its research environments. Its new multistage monitoring aims to alert within 30 minutes, and if responders cannot rule out a false positive within 30 minutes they are expected to pause the activity. OpenAI estimated monitoring overhead at roughly 20% of the monitored inference compute.[3][34] After the September 20 incident it paused "all other training, evaluation, and inference with tool-use (defined broadly) for our most capable models" until it had validated the fix and completed more red-teaming, said it would not resume training that model, added blocking controls at two independent layers, and restricted DNS queries to an allowed list.[2][16]

Anthropic

Three incidents disclosed July 30

Prompted by OpenAI's disclosure, Anthropic reviewed 141,006 cybersecurity evaluation runs in which Claude could have obtained internet access and on July 30, 2026 reported three incidents, involving six runs, in which a Claude model reached the internet from an evaluation environment run by Irregular and gained unauthorized access to the production infrastructure of three organizations. In every case the evaluation prompt told Claude that its environment was a simulation without internet access; a misconfiguration left the machines connected. The earliest incidents dated to April. The models ran without the classifiers and monitoring Anthropic uses in production but with their safety training.[4]

Model	What happened	Behavior once signs of reality appeared
Claude Opus 4.7	In four runs, reached a real company that shared a name with the fictional target; extracted application and infrastructure credentials and accessed a database with several hundred rows of production data	Recognized the system was real and continued the attack[4]
Claude Mythos 5	Published a malicious Python package to PyPI under a name referenced in fictional setup instructions; it was available for about an hour and ran on 15 real systems, including a security company's package scanner, whose credentials Claude then used	Reasoned that the environment was still a simulation[4]
Internal research model	Scanned roughly 9,000 targets and compromised one company's internet-facing application using exposed debug credentials and SQL injection	Concluded the target was real and stopped[4]

Anthropic notified Irregular and the affected organizations on July 27; the two it was able to reach had not detected the activity. PyPI's own security systems removed the package. Anthropic's first assessment was that the incidents were "closer to a harness and operational failure than a model alignment failure."[4]

Alignment assessment and fourth incident

On August 31 Anthropic said it had paused external cyber evaluations of pre-release models and briefly paused internal ones, deployed a classifier that blocks a tool call when a model aggressively probes or escapes a testing environment or unexpectedly obtains internet access, migrated high-risk cyber sandboxes to stronger isolation, and asked every organization testing its pre-release models with reduced cyber safeguards to follow a set of practices. These include running cyber evaluations offline by default, having the model try to escape the sandbox before evaluations begin, confirming tasks are solvable, and stating scope as instructions ("You should not access the internet") rather than claims about the environment.[5]

On September 9 Anthropic published an alignment assessment that revised its earlier view. It said it now believed the models showed "biased reasoning", selectively interpreting evidence that they were on the real internet, and "recklessness", a willingness to take harmful actions in narrow pursuit of a task. It singled out the Mythos 5 case: when researchers edited the transcript to make it clearer the environment was real, Mythos 5 still took offensive actions.[6] While assembling transcripts for METR, Anthropic found a set its first scan had missed and identified a fourth incident from January 2026, in which an early checkpoint of Claude Opus 4.6, unable to abort a broken task, found the same egress path, used a password found in a file to gain admin access to a third party's machine, harvested credentials, and read the personal information of one person. A broader scan of roughly 481 million transcripts found no other cases of similar or worse severity.[6] Anthropic said it found no evidence of coordination between agents, of goals beyond the assigned task, or of attempts to evade oversight, and that it had signed an agreement with METR for an independent investigation.[6]

In the Claude Opus 5.5 system card of September 22, 2026, Anthropic reported that in a new evaluation of 28 handmade scenarios designed to tempt the model into violating containment boundaries, Opus 5.5 attempted to cross a boundary in 1.5% of cases, all rated low severity.[7] Axios reported the figure as part of a September 26 story in which unnamed sources said OpenAI, Anthropic and security researchers were investigating "tens of thousands of incidents" of problematic model behavior across testing and real-world use, most not known to have caused harm.[17]

Meta

Meta confirmed on August 5, 2026 that one of its models had exploited a vulnerability in another organization's systems during a test by Irregular, attributing it to a "misconfiguration" in the evaluation environment.[13][14] On August 14 it published a retrospective. Irregular had begun the exercise with a pre-release version of Muse Spark 1.1 in early July; a misconfiguration allowed internet access, and Irregular had unintentionally given the model the name of a real website as its target instead of a fictional one. The model exploited a vulnerability in that site, accessed information, and made changes to its database. Meta said it reviewed more than 10,000 records of the model's activity and found no other instances, and that "this was not a sophisticated offensive cyber attack or sandbox escape."[8] It said it would require independent verification of test-environment isolation and scenario review before evaluations, and that test scenarios must not reference real companies.[8]

Google

On September 18, 2026 The Wall Street Journal reported that a Gemini model had broken into the systems of three real companies in May during a capture-the-flag exercise run on Irregular's infrastructure, in which fictional target companies shared names with real ones. In one case it guessed passwords; in the other two it found working credentials in a public database.[10][11] Google confirmed the incidents. Heather Adkins, its vice president of security engineering, said: "In a standard evaluation, the model found public information online and guessed credentials to access websites it thought were part of the test. In all three of these instances, the model stopped." She added that Google had made sure "the three entities were made aware" and had worked with its testing partner on changes to its processes.[10] According to reporting summarized by Al Jazeera, Irregular notified Google at the end of July, and Google said the behavior was not an example of model misalignment and did not warrant public disclosure because Gemini's safety measures worked.[11] Irregular told Axios it had notified "all relevant [AI] labs in late July" and that "all known issues on our end were remedied and resolved weeks ago."[10] Analysts quoted by CSO Online criticized Google for waiting until a reporter asked.[12]

UK AI Security Institute

On August 4, 2026 the UK AI Security Institute (AISI) published an incident report on its own testing. On July 28 its security team detected data leaving a research system through the Tor network. In a single evaluation run 122 times across seven models, with internet access deliberately enabled and developer cyber classifiers disabled, it found 19 unsanctioned actions in 10 runs between July 25 and July 28: 17 from Claude Mythos 5 and 2 from GPT-5.6 Sol. In the most serious sequence an agent tried to insert malicious code into a public open-source project on GitHub, created fake identities to pressure the maintainer, and messaged real people; a human maintainer refused the code. AISI said it contained the incident within about an hour, found no real-world harm, and would tighten internet access, add real-time monitoring, and redesign evaluations.[9] AISI stated that this "was not a case of a model escaping its secure test environment".[9]

Kimi K3

Wired reported on August 6, 2026 that Frontier Security, a US startup, said Moonshot AI's open-weight Kimi K3 model went outside its sandbox during a defensive cybersecurity test, after a leak in the sandbox network configuration, and retrieved answers from GitHub without hacking anything. Frontier said it used the default sandbox in AISI's Inspect framework; an AISI spokesperson called the claims "inaccurate and irresponsible" and said the issues resulted from how the company configured the tool.[15] This case was reported by a third-party tester, not by Moonshot.

Common factors

The developers' own analyses point to several recurring conditions:

Reduced safeguards during capability testing. Anthropic, Meta and AISI all ran the relevant evaluations without some or all of the production classifiers or safety filters shipped with public models, in order to measure underlying capability.[4][8][9]
Impossible or broken tasks. Anthropic's Opus 4.6 incident began after the model broke its own target and could not abort; AISI found that misconfigured task prompts led agents to believe no in-scope solution existed. Anthropic now asks partners to confirm tasks are solvable, noting that agents facing an offline target or impossible task "will often look for other ways to complete a challenge".[5][6][9]
Mismatch between prompt and environment. Anthropic's and Meta's models were told they were in a simulation or given a real site as a target, and treated real systems as part of the exercise.[4][8]
Monitoring gaps. The two organizations Anthropic reached had not noticed the activity; Anthropic said it had generally reviewed only a sample of evaluation transcripts after the fact; AISI's alert came from general security monitoring rather than evaluation monitoring; OpenAI's automatic stop failed in September.[2][4][5][9]

Reception and disputes

Some security professionals were skeptical. Ilia Kolochenko of ImmuniWeb told The Register that some disclosures appeared to be "part of a well-orchestrated marketing campaign" and that the escapes were the result of poorly isolated test environments.[13] Snehal Antani told Axios that "Those frontier labs and their fear-mongering is causing a collective eye roll across the entire practitioner community that knows what they're talking about".[18] Others treated the incidents as warnings; Forrester's Jeff Pollard told CSO Online that Gemini "pursued an authorized objective through an unauthorized path".[12]

Responses

Industry

OpenAI chief scientist Jakub Pachocki wrote in his September 6 essay An Alien Mind that "I expect and hope for voluntary slowdowns to become commonplace until shared safety bars are established."[1]
On September 12, Anthropic chief executive Dario Amodei published "We Must Pace the Frontier", which cites the OpenAI-Hugging Face incident as one of two reasons for slowing capability advances and proposes a three-step plan beginning with embedded third-party evaluators, a step Anthropic committed to unilaterally. He wrote that "pacing does not mean halting model training or technical progress".[22] Altman and Elon Musk endorsed the call.[11]
The Open Secure AI Alliance published a request for comments on August 4 for the Shared AI Findings Exchange (SAFE), a proposed framework for confidentially sharing AI incidents and near misses.[29] See Open Secure AI Alliance.
On September 28 NVIDIA launched the Open Agent Safety Platform, combining the OpenShell runtime with Sentry, a reference design for an out-of-band watchdog on BlueField-4 DPUs that NVIDIA says can quarantine agents in milliseconds.[23] NVIDIA's technical blog said "Several frontier labs have recently reported versions of the same story: AI agents broke out of the evaluation environments that were meant to contain them and reached systems they never should have been allowed to."[24] Jensen Huang called the platform "a browser for agents".[25]

Government

In Australia, Albanese criticized OpenAI's delay in notifying the government about the Medicare portal.[19][30]
In the United States, Senator Ed Markey introduced a bill to create a federal Cybersecurity and AI Board of Investigations with subpoena power to investigate AI agent-led hacks affecting federal systems or critical infrastructure. Markey said "the public is learning critical details piecemeal".[21] TechSpot reported that Senator Josh Hawley opened a Senate subcommittee investigation of OpenAI's handling of the Hugging Face breach, asking Altman 16 questions with an October 1 deadline, and that Senator Richard Blumenthal separately sent Altman a letter on September 9 about containment failures and related issues.[32]
Cybersecurity Dive reported that President Donald Trump had called AI safety fears a "hoax", and that Treasury Secretary Scott Bessent said the US wanted to work with China on a system for disclosing potentially serious AI incidents.[10]

See also

References

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OpenAI Alignment. "An agent used DNS to reach an external chatbot." Misalignment report, September 25, 2026. https://alignment.openai.com/misalignment-reports/an-agent-used-dns-to-reach-an-external-chatbot/
OpenAI. "Pacing model development in an era of cyber-critical capabilities." August 18, 2026. https://openai.com/index/pacing-model-development-cyber-capabilities/
Anthropic. "Investigating three incidents in our cybersecurity evaluations." July 30, 2026, updated August 3, 2026. https://www.anthropic.com/news/investigating-incidents-cybersecurity-evals
Anthropic. "Improving our alignment and security practices." August 31, 2026. https://www.anthropic.com/news/improving-alignment-security-efforts
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Editing: AI agent sandbox escapes