All news with #prompt injection attack tag

🛡️ A Gartner survey found 29% of security leaders reported generative AI applications in their organizations were targeted by cyberattacks over the past year, and 32% said prompt-structure vulnerabilities had been deliberately exploited. Chatbot assistants are singled out as particularly vulnerable to prompt-injection and hostile prompting. Additionally, 62% of companies experienced deepfake attacks, often combined with social engineering or automated techniques. Gartner recommends strengthening core controls and applying targeted measures for each new risk category rather than pursuing radical overhauls. The survey of 302 security leaders was conducted March–May 2025 across North America, EMEA and Asia‑Pacific.

⚠️ Researchers at Noma Security disclosed a critical 9.4-severity vulnerability called ForcedLeak that affected Salesforce's AI agent platform AgentForce. The chain used indirect prompt injection via Web-to-Lead form fields to hide malicious instructions within CRM data, enabling potential theft of contact records and pipeline details. Salesforce has patched the issue by enforcing Trusted URLs and reclaiming an expired domain used in the attack proof-of-concept. Organizations are advised to apply updates, audit lead data for suspicious entries, and strengthen real-time prompt-injection detection and tool-calling guardrails.

⚠️ Salesforce has released patches for a critical prompt-injection vulnerability dubbed ForcedLeak that could allow exfiltration of CRM data from Agentforce. Discovered and reported by Noma Security on July 28, 2025 and assigned a CVSS score of 9.4, the flaw affects instances using Web-to-Lead when input validation and URL controls are lax. Researchers demonstrated a five-step chain that coerces the Description field into executing hidden instructions, queries sensitive lead records, and transmits the results to an attacker-controlled, formerly allowlisted domain. Salesforce has re-secured the expired domain and implemented a Trusted URL allowlist to block untrusted outbound requests and mitigate similar prompt-injection vectors.

🔒 A critical vulnerability in Salesforce Agentforce allowed malicious text placed in Web-to-Lead forms to act as an indirect prompt injection, tricking the AI agent into executing hidden instructions and potentially exfiltrating CRM data. Researchers at Noma Security showed attackers could embed multi-step payloads in a 42,000-character description field and even reuse an expired whitelisted domain as a data channel. Salesforce patched the issue on September 8, 2025, by enforcing Trusted URL allowlists, but experts warn that robust guardrails, input mediation, and ongoing agent inventorying are needed to mitigate similar AI-specific risks.

🛡️ A Gartner survey finds 62% of organisations experienced a deepfake attack in the past 12 months, with common techniques including social-engineering impersonation and attacks on biometric verification. The report also shows 32% of firms faced attacks on AI applications via prompt manipulation. Gartner’s Akif Khan urges integrating deepfake detection into collaboration tools and strengthening controls through awareness training, simulations and application-level authorisation with phishing-resistant MFA. Vendor solutions are emerging but remain early-stage, so operational effectiveness is not yet proven.

🔒 CrowdStrike announced its intent to acquire Pangea to deliver the industry’s first AI detection and response (AIDR) capability, securing enterprise AI use and development across data, models, agents, identities, infrastructure, and interactions. Unveiled at Fal.Con 2025 by Michael Sentonas, the deal will integrate Pangea’s prompt‑layer and interaction security with the Falcon platform to provide unified visibility, governance, and enforcement across the AI lifecycle. The combined solution targets prompt injection, model manipulation, shadow AI and sensitive data exfiltration while enabling developers and security teams to innovate faster with built‑in safeguards.

🔒 An AI-integrated browser embeds large multimodal models into standard web browsers, allowing agents to view pages and perform actions—opening links, filling forms, downloading files—directly on a user’s device. This enables faster, context-aware automation and access to subscription or blocked content, but raises substantial privacy and security risks, including data exfiltration, prompt-injection and malware delivery. Users should demand features like per-site AI controls, choice of local models, explicit confirmation for sensitive actions, and OS-level file restrictions, though no browser currently implements all these protections.

🛡️ Enterprises now face attackers embedding malicious prompts in document macros and hidden metadata to manipulate generative AI systems that parse files. Researchers and vendors have identified exploits — including EchoLeak and CurXecute — and a June 2025 Skynet proof-of-concept that target AI-powered parsers and malware scanners. Experts urge layered defenses such as deep file inspection, content disarm and reconstruction (CDR), sandboxing, input sanitization, and strict model guardrails to prevent AI-driven misclassification or data exposure.

🔓 Oasis Security disclosed a flaw in Cursor that allows malicious repositories to execute code when a developer opens a folder. The vulnerability stems from Workspace Trust being disabled by default, permitting crafted .vscode/tasks.json entries set to run on folder open to autorun without prompting. Successful exploitation can expose API keys, cloud credentials and local secrets, risking organization-wide compromise.

🔒 Researchers disclosed linked phishing campaigns delivering a banking malware-turned-RAT called MostereRAT and a ClickFix-style chain distributing MetaStealer. Attackers use an obscure Easy Programming Language (EPL), mutual TLS for C2, and techniques to disable Windows security and run as TrustedInstaller to evade detection. One campaign drops remote-access tools like AnyDesk and VNC variants; another uses fake Cloudflare Turnstile pages, LNK tricks, and a prompt overdose method to manipulate AI summarizers.

🤖 In episode 433 of Smashing Security, Graham Cluley and Mark Stockley examine how attackers are weaponizing AI, from embedding malicious instructions in legalese to using generative agents to automate intrusions and extortion. They discuss LegalPwn prompt-injection tactics that hide payloads in comments and disclaimers, and new findings from Anthropic showing AI-assisted credential theft and custom ransomware notes. The episode also includes lighter segments on keyboard history and an ingenious AI-generated CAPTCHA.

🛡️ Guardio Labs researcher Nati Tal reported that threat actors are abusing Grok, X's built-in AI assistant, to surface malicious links hidden inside video ad metadata. Attackers omit destination URLs from visible posts and instead embed them in the small "From:" field under video cards, which X apparently does not scan. By prompting Grok with queries like "where is this video from?", actors get the assistant to repost the hidden link as a clickable reference, effectively legitimizing and amplifying scams, malware distribution, and deceptive CAPTCHA schemes across the platform.

🛡️ A recent proof-of-concept by Bargury demonstrates a practical and stealthy prompt injection that leverages a poisoned document stored in a victim's Google Drive. The attacker hides a 300-word instruction in near-invisible white, size-one text that tells an LLM to search Drive for API keys and exfiltrate them via a crafted Markdown URL. Schneier warns this technique shows how agentic AI systems exposed to untrusted inputs remain fundamentally insecure, and that current defenses are inadequate against such adversarial inputs.

🔐 Microsoft outlines practical guidance for securing and governing the emerging class of autonomous agents. Igor Sakhnov explains how agents—now moving from experimentation into deployment—introduce risks such as task drift, Cross Prompt Injection Attacks (XPIA), hallucinations, and data exfiltration. Microsoft recommends starting with a unified agent inventory and layered controls across identity, access, data, posture, threat, network, and compliance. It introduces Entra Agent ID and an agent registry concept to enable auditable, just-in-time identities and improved observability.

🛡️ Cloudflare has integrated unsafe content moderation into Firewall for AI, using Llama Guard 3 to detect and block harmful prompts in real time at the network edge. The model-agnostic filter identifies categories including hate, violence, sexual content, criminal planning, and self-harm, and lets teams block or log flagged prompts without changing application code. Detection runs on Workers AI across Cloudflare's GPU fleet with a 2-second analysis cutoff, and logs record categories but not raw prompt text. The feature is available in beta to existing customers.

⚠️ Unit 42 researchers Tony Li and Hongliang Liu introduce Logit-Gap Steering, a new framework that exposes how alignment training produces a measurable refusal-affirmation logit gap rather than eliminating harmful outputs. Their paper demonstrates efficient short-path suffix jailbreaks that achieved high success rates on open-source models including Qwen, LLaMA, Gemma and the recently released gpt-oss-20b. The findings argue that internal alignment alone is insufficient and recommend a defense-in-depth approach with external safeguards and content filters.

🔐 Palo Alto Networks and Portkey have integrated Prisma AIRS directly into Portkey’s AI gateway to embed security guardrails at the gateway level. The collaboration aims to protect applications from AI-specific threats—such as prompt injections, PII and secret leakage, and malicious outputs—while preserving Portkey’s operational benefits like observability and cost controls. A one-time configuration via Portkey’s Guardrails module enforces protections without code changes, and teams can monitor posture through Portkey logs and the Prisma AIRS dashboard.

🔒 Microsoft outlines a layered defense-in-depth strategy to protect systems using LLMs from indirect prompt injection attacks. The approach pairs preventative controls such as hardened system prompts and Spotlighting (delimiting, datamarking, encoding) to isolate untrusted inputs with detection via Microsoft Prompt Shields, surfaced through Azure AI Content Safety and integrated with Defender for Cloud. Impact mitigation uses deterministic controls — fine-grained permissions, Microsoft Purview sensitivity labels, DLP policies, explicit user consent workflows, and blocking known exfiltration techniques — while ongoing research (TaskTracker, LLMail-Inject, FIDES) advances new design patterns and assurances.