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CategoryAll Exploit / PoC 7 AI industry 5 Tools 4 Vulnerability 3 Industry 3 Advisory 2 Threat actor 2 Data breach 2 Policy & legal 2 Model release 1 AI tools & infra 1 AI safety & security 1 AI policy 1 Malware 1

SeverityAll critical 5 high 6 medium 5 low 1 info 19

When scanners miss the attack: how Cloudflare Client-Side Security protects storefronts

Cloudflare's Page Shield ML uncovered four malicious JavaScript campaigns on storefronts, including affiliate fraud and a remote-backdoor script, that VirusTotal and URLScan missed.

Cloudflare's Page Shield ML detected four client-side JavaScript operations (eight payloads) in live traffic on online storefronts, enabling affiliate commission hijacking, clickless affiliate theft via hidden iframes, user tracking with a remote-code backdoor, and cloaking of paid mobile visitors. Seven of the eight payloads were absent from VirusTotal and URLScan returned no malicious verdict for any, including a Lnkr-family payload indexed unclassified for roughly 2.5 years. Detection relies on a graph neural network over JavaScript syntax trees, an LLM second opinion on Workers AI, and a frontier-model ensemble voting across benign, magecart, other malware, and cryptomining labels.

Cloudflare BlogSep 16, 20:06 UTC · 10h agoMalware in the wild

First Agentic AI Data Breach Reported to Spanish Regulator

Spain's AEPD reported the first data breach executed by an AI agent, which autonomously chained login, vulnerability discovery, and personal data modification.

Spain's Data Protection Agency (AEPD) published details of the first breach notification in which an AI agent executed the attack, achieving a successful login, searching for vulnerabilities, and modifying personal data and accessing invoices. The agency called the agent's autonomous chaining of attack phases a qualitative change and urged updated risk analysis, faster incident response, and stronger credential protection. Investigation is ongoing; commentators cite possible causes including a guardrail jailbreak, an escaped test model, or an unauthorized LLM-based penetration test.

SecurityWeekSep 16, 16:39 UTC · 13h agoData breach in the wild 2 sources1· 1 read

Spain gets its first taste of AI-aided cyber attack

Spain's AEPD reports the country's first data breach executed by an autonomous AI agent that scanned files and exploited vulnerabilities to access personal data.

Spain's data protection agency AEPD reported the country's first personal data breach caused by an autonomous AI agent powered by a known large language model. The agent scanned generic files, accessed the organization's system, and ran vulnerability scans to gain read/write access to files containing personal data and invoices. AEPD president Francisco Pérez Bes called for an immediate review of security and data protection models, noting the agency received a record 30,931 complaints in 2025, up 64% year-over-year.

The Register · SecuritySep 16, 11:56 UTC · 18h agoAI safety & security in the wild1

Parallels Desktop Flaw Lets Non-Admin Mac Users Gain Root, but Intel Macs Can't Install Fix

JFrog disclosed CVE-2026-90894, a 7.8-rated local privilege escalation in Parallels Desktop for Mac, patched only in version 27, which Intel Macs cannot install.

JFrog researcher Yuval Moravchick disclosed CVE-2026-90894 (dubbed ParaShells, CVSS 7.8), a local privilege escalation in Parallels Desktop for Mac that lets non-admin users run code as root. The root-level prl_disp_service listens on a world-writable socket, and argument injection into a tar command via QProcess::splitCommand and the --use-compress-program option yields code execution as root, demonstrated on Parallels Desktop 26.4.0 build 57513 on Apple silicon. The fix appears in version 27.0.0, but Parallels Desktop 27 requires Apple silicon, leaving Intel Macs on the 26.x line with no build JFrog describes as fixed. No exploitation in the wild has been reported and Parallels has not published a statement.

The Hacker NewsSep 16, 13:14 UTC · 17h agoVulnerability 4 sources CVE-2026-90894

Hackers Got Inside a Flock Camera. Its Data Shows How the System Really Works

Hackers stole a Flock Safety camera, copied its storage, and recovered an encryption key exposing vehicle surveillance data and system internals.

Hackers from the collective stegan0gram removed a Flock Safety license plate reader from a roadway, copied its storage, and recovered an encryption key stored in an unencrypted partition, unlocking videos of thousands of vehicle detections. The data, shared with 404 Media, WIRED, and Distributed Denial of Secrets, shows the camera generated roughly 1.6 million images of about 50,200 vehicles over 21 days and detects people, bicycles, and bumper stickers in addition to license plates. The dump follows 2025 research by Jon 'GainSec' Gaines documenting flaws enabling root access, which Flock downplayed. Flock's national network makes camera records searchable by more than 2,000 agencies, fueling controversy over police and immigration lookups.

WIRED · Securityupdated Sep 16, 22:19 UTC · 8h agofirst Sep 16, 10:30 UTC · 20h agoData breach in the wild 3 sources