AntiMalwareJuly 17, 2026🇷🇺Translated from Russian

One in Five Data Leaks Now Linked to Shadow AI Usage as Employees Feed Sensitive Corporate Data into Public AI Services

Small and medium-sized businesses as well as large corporations are increasingly exposed to data leaks caused by employees’ unauthorized use of generative AI tools. Security teams are struggling to keep pace as staff send internal information to public neural networks faster than information security departments can identify the new risk vectors.

According to research by Informzashchita, in July 2026 already 20% of organizations that suffered data leaks were able to link at least part of the incidents to unsanctioned GenAI usage. One year earlier the figure stood at approximately 12%. These cases go far beyond simply asking a chatbot to edit an email.

Employees are uploading contracts, source code, internal correspondence, client inquiries, and technical documentation to public AI services. The study breaks down the primary vectors responsible for these leaks:

  • 42% occur through public AI web interfaces;
  • 24% are connected to browser extensions and AI assistants that gain access to tabs, session history, and cookies;
  • 19% result from independently connected APIs and libraries;
  • 15% involve tools designed for programmers.

Traditional security controls frequently fail to detect the activity because the domains are legitimate, TLS encryption is active, and no malware signatures are present. As a result, confidential documents are exfiltrated to external services without triggering alerts.

The research also found that nearly one-third of companies using AI have discovered at least one API key or secret stored in insecure locations such as configuration files, test scripts, workstations, and Git repositories. Attackers who obtain these credentials can not only consume the organization’s AI budget but also reach connected databases and RAG data stores.

Late detection significantly increases the financial impact: incidents involving shadow AI raise average breach costs by roughly $670,000. Experts advise organizations to begin with comprehensive service inventories, secret scanning, browser-extension governance, and data classification instead of attempting to ban tools such as ChatGPT by policy alone.

Related articles

BoletimSecAI Security

AgentForger Vulnerability in ChatGPT Workspace Agents Enabled Malicious AI Deployment via Single Phishing Link

A vulnerability in ChatGPT Workspace Agents allowed attackers to create and deploy a malicious AI agent inside an organization from a single phishing link. Named AgentForger, the flaw was fixed by OpenAI on June 8, 2026. The attack exploited a permissive parameter in the Agent Builder that accepted instructions directly through the URL. An authenticated user opening the prepared link would trigger automatic execution of the command without additional confirmation. The victim required access to Workspace Agents and at least one pre-authorized enterprise connector such as Outlook, Gmail, Google Drive, Slack, Teams, or Google Calendar. The malicious prompt instructed the platform to create an agent, connect available applications, disable approval requests, publish the component, and schedule it for recurring operation. In the demonstration, the agent monitored emails from the attacker with subjects starting with “TASK” and executed the contained instructions while returning results to the attacker-controlled address.

安全客AI Security

AI Coding Tools Under Fire: Grok Build Uploads Entire Git Histories, Claude Code Suspected of Silent Transfers

Security researcher cereblab uncovered that Grok Build 0.2.93 establishes separate HTTPS channels to exfiltrate full Git repositories, resulting in a 27800-fold traffic discrepancy between task context and storage uploads to Google Cloud Storage buckets. The tool ignores user instructions such as "do not read" and decouples the improve_model_enabled client switch from the server-controlled trace_upload_enabled flag, allowing continued uploads even when privacy settings are disabled. Similar concerns emerged around Claude Code, which maintains undisclosed WebSocket connections that transmit file paths, dependency trees, and code metadata without user awareness or audit logs. Comparative traffic audits showed that Codex and Gemini produced no anomalous outbound activity, while Grok Build and Claude Code were the only tools confirmed to perform data transfers beyond user authorization. The incidents highlight systemic issues including server-side remote control of client behavior, lack of third-party audits for closed-source binaries, and the conflict between model training data needs and user data sovereignty. Experts recommend zero-trust measures such as network blocking, Docker sandboxing without mounting .git directories, git filter-repo sanitization, and preference for auditable open-source alternatives like Continue.dev or locally deployed Ollama models.

安全客AI Security

PentesterFlow Launches Open-Source AI CLI Tool for Penetration Testers and Bug Bounty Hunters

PentesterFlow is a new open-source, human-in-the-loop AI command-line tool designed specifically for penetration testers and bug bounty hunters. It automates the full workflow from reconnaissance to report generation while requiring explicit analyst approval before executing sensitive commands. The tool addresses common issues in agentic AI security tools such as hallucinations, weak context retention, and poor tool integration by incorporating built-in pentesting skills and evidence-based vulnerability confirmation. It supports connections to local or hosted LLMs including Ollama, Gemini, Groq, and others, and features continuous local learning that stores user preferences and lessons without retraining models. A key differentiator is its integration with Burp Suite and a permission-based execution model that includes a YOLO mode for isolated environments. The project positions itself as a transparent alternative to fully autonomous tools like PentAGI and PentestGPT.

SecuritylabAI Security

Optimizing Cybersecurity Content for LLMs: How Sites Can Enter Generative AI Answers

Search engines and AI services like ChatGPT, Gemini, Perplexity, Copilot and Google AI Overviews increasingly deliver synthesized answers instead of link lists. For cybersecurity publishers this changes competition because high traditional rankings no longer guarantee visibility or accurate citation. The article explains GEO, AEO and LLMO practices, shows how material moves through indexing, fragment selection and summarization stages, and stresses the need for self-contained facts that survive extraction and paraphrasing. It provides concrete writing frameworks for vulnerability reports, including required fields such as CVE identifiers, affected versions, attack conditions and real-world exploitation evidence. Technical requirements cover correct robots.txt handling for Googlebot, OAI-SearchBot, GPTBot and Bingbot plus the use of IndexNow for rapid updates. The piece also warns about poisoning risks, prompt injection and slopsquatting attacks that can feed false data into generative systems.