Natalia Kasperskaya Advises Against Mass Biometric Rollout in Russia Citing High Costs, Reliability Issues and Deepfake Threats
Natalia Kasperskaya, president of InfoWatch and chair of the board of the Domestic Software association, has cautioned against the indiscriminate rollout of biometric authentication systems throughout Russia, describing the approach as both costly and insufficiently secure.
In an interview with TASS, Kasperskaya stated that mass adoption of biometrics represents an expensive and not particularly reliable undertaking. She recommended restricting its use to selected processes and employing it solely as an additional layer of identity verification rather than a universal solution.
One of the principal obstacles, she noted, is the substantial financial outlay required. Facial recognition systems generate a digital model of a person’s face using thousands of reference points. Face ID, for example, projects more than 30,000 invisible points onto the user’s face. Scaling comparable technology nationwide would demand significant computational resources and vast data-storage infrastructure.
Practical challenges further complicate deployment. Biometric performance depends heavily on camera quality, lighting conditions and the clarity of the original image. Attempts to enrol or authenticate using older smartphones in dimly lit environments frequently fail to produce usable results.
An additional and increasingly serious threat comes from deepfakes. Artificial images and videos are becoming progressively more convincing, to the point where the human eye can no longer reliably differentiate between genuine photographs and sophisticated fakes. This development complicates identity verification and creates fresh opportunities for fraudsters.
Consequently, Kasperskaya sees no justification for positioning biometrics as a universal key for all services. In her view, the technology should be applied selectively and should complement, rather than replace, existing identification methods.
Russia already operates the Unified Biometric System, which allows citizens to access Gosuslugi, obtain electronic signatures or eSIM cards, and perform certain banking operations such as opening accounts or obtaining loans.
Related articles
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.
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.
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.
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.