AI Sec Watch

NCorr-FP is a data fingerprinting (embedding hidden recipient-specific marks into data to track ownership) technique designed to protect structured tabular data in shared environments. The method preserves the statistical quality of data while embedding fingerprints using local record similarity and density estimation, and can detect these fingerprints even after substantial data modification or deletion attacks.

A vulnerability exists in ONNX MLIR (a tool that converts machine learning models to code) versions up to 0.5.0.0 where the generate_hash_key function uses a weak hash (a simple algorithm for converting data into a fixed-length code that is easy to reverse or predict). The vulnerability requires local access to exploit and is difficult to execute in practice.

This cybersecurity news roundup covers several major threats: attackers are poisoning AI chatbot search results to trick users into downloading malware that hijacks computer power for cryptocurrency mining; the Grandoreiro banking trojan continues targeting financial institutions despite being a decade old; and a ransomware group called The Gentlemen uses self-propagating malware to automatically encrypt entire networks. Additionally, Let's Encrypt is preparing to adopt Merkle Tree Certificates (a more efficient way to batch multiple digital certificates under one signature) to handle the larger file sizes of post-quantum cryptography, with a test environment launching in late 2026.

Attackers exploited Meta's AI customer support agent by tricking it into linking Instagram accounts to email addresses they controlled, showing that AI security risks extend beyond sophisticated attacks to simple social engineering exploits. Psychologist Gloria Mark warns that relying on AI chatbots like ChatGPT and Claude may weaken human attention spans, critical thinking, and emotional intelligence by deferring cognitive work to machines.

Despite rapid adoption of AI tools in security operations centers (SOCs, teams that monitor and respond to security threats), only 10% report excellent value from these investments. The problem is structural: most SOCs deploy off-the-shelf AI without customization or best practices, and individual AI tools don't share information with each other, so analysts still face fragmented workflows even though individual tasks run faster.

Anthropic, an AI company, has filed for an initial public offering (IPO, the process of selling company shares to the public for the first time) with a $965 billion valuation and $47 billion revenue run rate, setting up a major test of whether sky-high valuations for AI companies are justified. Analysts say the key metric determining Anthropic's success won't be its valuation but its gross margin (the percentage of revenue left after paying the costs to provide AI services), which the company has kept secret and will likely reshape how the entire industry is valued. The filing could have major impacts on competitors and how enterprises price AI services going forward.

Attackers exploited Meta's AI customer support agent by simply asking it to link Instagram accounts to email addresses they controlled, allowing them to steal accounts including a high-profile one. The hack shows that while AI security discussions often focus on powerful AI systems attacking computer infrastructure, the real vulnerability here was that the AI agent itself became a target through direct, straightforward manipulation that should have been caught before deployment.

Claude Code, Anthropic's AI coding assistant, stores OAuth tokens (security credentials that prove access permission) in plaintext in a configuration file, and researchers discovered an attack where malicious npm packages (JavaScript libraries) can silently redirect these tokens to attacker-controlled servers before they reach legitimate services like GitHub or Jira. The attack is difficult to detect because the requests appear legitimate in audit logs, and Anthropic has not released a patch despite knowing about the vulnerability since April.

AI tools are being sold increasingly on underground ransomware marketplaces, with sales growing from 38 posts in December 2025 to 1,486 in February 2026. These tools include weaponized LLMs (large language models without safety protections), deepfakes for identity fraud, AI-enhanced malware, and stolen AI accounts, making it easier for criminals to launch attacks at scale. The source notes that while criminal security is weaker than it appears and criminals sometimes steal from each other, ransomware attacks have grown 20% since 2023 and become significantly more profitable.