SQL injection vulnerability
SQL injection vulnerability
The Security Gaps New AI Attacks Expose
AI attacks can change faster than security rules. Novel prompts, unexpected model behavior, and new attack paths can bypass controls built around threats you've already seen
Known Rules Can't Catch Every New Attack
Traditional security controls often depend on known patterns, signatures, or predefined rules. A new AI attack can use unfamiliar instructions or behavior that doesn't match anything your security team has previously identified.
Malicious Inputs Can Look Completely Legitimate
A zero-day AI attack doesn't need to look obviously malicious. It can be disguised as a normal request, embedded in retrieved content, or designed to trigger only under specific conditions, making simple pattern-based detection harder.
AI Behavior Can Change Across Contexts
The same input can produce different behavior depending on the model, conversation history, retrieved data, tools, or application context. An attack that appears harmless in isolation can become dangerous when combined with the rest of the AI workflow.
New Attack Paths Can Emerge After Deployment
AI applications continuously change as models, prompts, tools, integrations, and data sources are updated. A previously safe workflow can develop a new security weakness without any obvious change to traditional infrastructure.
AI Is Changing the Zero-Day Threat Landscape
AI systems are finding unknown vulnerabilities, exploiting unfamiliar attack paths, and taking actions at machine speed. The window between discovery and exploitation is getting harder to defend.
High- and critical-severity zero-days identified by Anthropic’s Project Glasswing during its first month of testing.
Of tested zero-days produced a working exploit on the first attempt, according to Project Glasswing findings.
Autonomous actions were reconstructed in an AI-driven attack on Hugging Face before the activity was detected.
Of AI-assisted vulnerabilities identified in early 2026 were confirmed to have been exploited in the wild.
How LangProtect Secures AI Against Emerging Threats
LangProtect analyzes AI interactions in real time, combining contextual inspection, security policies, and behavioral signals to identify suspicious activity even when the exact attack pattern is new.
Detect Unknown Attack Patterns
Identify suspicious AI interactions that don't match previously known signatures or attack rules. LangProtect evaluates the context and behavior of an interaction to surface emerging threats before they can spread.
Inspect AI Inputs and Outputs
Analyze prompts, retrieved content, model responses, and other AI interactions for unexpected or malicious behavior. This helps uncover attack techniques that may appear harmless when viewed as isolated inputs.
Identify Anomalous AI Behavior
Look for behavior that deviates from the application's expected security policies or operating context. Unexpected requests, unusual data access, or suspicious interaction patterns can become signals for further inspection.
Block Emerging Threats in Real Time
Apply security policies while the AI interaction is happening. When an interaction is identified as unsafe or violates policy, LangProtect can block or intervene before the activity reaches downstream systems or users.
Track and Investigate New Threats
Maintain visibility into detected threats, affected interactions, policy decisions, and enforcement actions. Security teams can use this context to investigate emerging attack patterns and strengthen controls as new techniques evolve.
How LangProtect Stays Ahead of Emerging AI Threats
Detect Emerging Threats
Identify novel attack patterns that traditional security controls may miss.
Monitor and Stop Threats
Inspect AI interactions for suspicious activity and block unsafe requests in real time.
Strengthen Protection Over Time
Use threat insights and enforcement records to refine security policies as attack techniques evolve.
Stay Ahead of the Next AI Threat
Detect, contain, and respond to emerging AI threats before unknown attack techniques become enterprise incidents.