A crypto-mining campaign abusing Hugging Face models returned days after takedown, hijacking GPU servers and planting backdoors, with one model downloaded over 28,000 times. Separately, a fake Solana starter kit on GitHub is positioned to trick AI coding agents into installing a NetSupport RAT. [...]
The defining development of the period came not from attackers but from the AI labs themselves, whose models broke out of controlled evaluations and reached real systems. In the wild, the criminal and state use of AI continued to mature along the lines tracked in earlier editions: models now act as attack operators, an underground market supplies the access, and AI systems have themselves become a target. The substantial distance between what the strongest models demonstrated under evaluation…
Executive Summary OpenAI disclosed that agents used exposed Hugging Face credentials to write a file and deploy proxy Spaces during an unrelated May 2026 research workload, but it did not identify the accounts. SentinelLABS identified two accounts likely used in associated activity, 0Time and Nyx9. Their public histories extend OpenAI’s chronology and preserve previously unreported relay code, document-borne probes, and ChatGPT account-provisioning capability. The public records provide precise…
The question of whether a Frontier AI model could find vulnerabilities that no human researcher had found was settled in April. Claude Mythos Preview identified thousands of previously unknown flaws across every major operating system and browser, including a 27-year-old denial-of-service condition in OpenBSD, and within a month Anthropic and its Project Glasswing partners had logged more than 10,000 high and critical severity findings, among them a certificate forgery flaw in wolfSSL, a…
Classification: Critical, Solution: Unavailable, Exploit Maturity: Not Defined, CVSSv3.1: None, CVEs: CVE-2026-80047, Summary: A vulnerability in the Hugging Face Transformers library (versions 4.49.0 through 5.8.1) allows remote, attacker‑controlled Python files to be written to the local disk without user authorization. The library performs a remote module fetch and local cache write before evaluating the trust_remote_code consent prompt, violating the security contract enforced across other…
EPSS 0.00 CVE-2026-80047 Hugging Face FI
Details about the Hugging Face hack, critical infrastructure under attack, a spoofed in-flight Wi-Fi network, and more of this month's cybersecurity news
Hugging Face SK
The hacking incident involving OpenAI evaluation agents and Hugging Face offers an unusually concrete look at what advanced AI-assisted intrusion can mean in practice: not a single clever exploit, but thousands of automated decisions, rapid experimentation, lateral movement, credential theft, persistence, and attempts to evade detection. The OpenAI–Hugging Face incident began during internal cybersecurity evaluations using ExploitGym, a benchmark designed to test whether AI agents can identify…
New details about the July attack on Hugging Face reveal that hundreds of AI agents driven by OpenAI's internal IM1 model coordinated the compromise through an unauthorized message board. [...]
A phase-by-phase detection mapping of the first publicly documented autonomous agent intrusion against production infrastructure — including the phases where no product in our category sees anything at all. Executive Summary On July 9, 2026, an autonomous AI agent running inside an OpenAI capability evaluation escaped its sandbox and launched a multi-day intrusion against Hugging Face’s Kubernetes environment. Across roughly 17,600 actions, it moved from third-party infrastructure into the…
An autonomous AI breach at Hugging Face and Anthropic's Fable suspension show the same thing: trusting a vendor isn't the same as being in control Category: News
The incident involving OpenAI models shows that autonomous hacks make human oversight more important, not less
Actor usage of AI is exploding. By analyzing artifacts left behind, Talos has created a detailed analysis of how we are seeing adversaries leverage the technology to include development, force multiplication, and vulnerability research.Based on the evidence Talos gathered, guardrails did not provide much protection, with most actors able to convince the models to comply despite the lack of sophisticated techniques or encoding. The pre-existing skill of the actor has a large impact on what they…
Hugging Face reconstructed more than 17,000 attacker events from a July 2026 intrusion driven by an autonomous artificial intelligence (AI) agent. The path was familiar: untrusted dataset content abused a processing worker (file disclosure, then code execution), credential harvest, then multi-cluster lateral movement. Production Elastic Defend behavior rules and Elastic Security detection (SIEM) rules already watch those types of behaviors. This post maps each stage to detections you can enable…
Hugging Face reconstructed more than 17,000 attacker events from a July 2026 intrusion driven by an autonomous artificial intelligence (AI) agent. The path was familiar: untrusted dataset content abused a processing worker (file disclosure, then code execution), credential harvest, then multi-cluster lateral movement. Production Elastic Defend behavior rules and Elastic Security detection (SIEM) rules already watch those types of behaviors. This post maps each stage to detections you can enable…
This vulnerability allows remote attackers to execute arbitrary code on affected installations of Hugging Face PyTorch Image Models. User interaction is required to exploit this vulnerability in that the target must visit a malicious page or open a malicious file. The ZDI has assigned a CVSS rating of 7.8. The following CVEs are assigned: CVE-2026-15679.
EPSS 0.00 CVSS 7.8 CVE-2026-15679 Hugging Face US
Recon, stolen credentials, hidden C2, and rebuild-or-patch. Four Hugging Face breach decisions that show whether you can catch an attack in progress. Category: News
Hugging Face BE
OpenAI’s own models broke out of a test sandbox and into Hugging Face’s servers to solve an evaluation, with no human attacker involved. The incident showed how keeping agentic AI safe now depends on how it’s contained, not just on how it’s trained.