AI security visualization with digital network overlays
AI Security R&D + Operations

Solving Complex AI Security Problems With Evidence

Obscurity Labs blends adversarial testing, control engineering, and incident readiness across AI-enabled systems. Our approach is informed by active R&D, including a living risk matrix that maps attack paths to concrete control and verification strategies.

Talk With AI Security TeamBack to Cyber Overview
LLM ApplicationsRAG PipelinesAgentic WorkflowsModel Supply ChainAI Incident Response

How We Work

From Security Research to Engineering Action

Our AI security engagements focus on turning complex threats into concrete decisions, validated controls, and measurable risk reduction.

Complex AI Threat Modeling

We map trust boundaries across prompts, tools, model artifacts, identity delegation, memory, and infrastructure.

  • Mission-specific abuse path inventory
  • Priority alignment by impact, not just CVSS-style severity
  • Architecture decisions tied to risk ownership

Adversarial Validation and Red Teaming

We emulate realistic attack behavior across AI-enabled business workflows, not isolated model endpoints.

  • Prompt, retrieval, and tool abuse scenario execution
  • Evidence-backed exploit chains for engineering teams
  • Verification tests for guardrail and control confidence

Control Engineering and Hardening

We design and validate policy controls, runtime constraints, and identity boundaries to reduce blast radius.

  • Least-privilege action and tool policies
  • Runtime and egress constraints for high-risk capabilities
  • Control implementation guidance with retest criteria

Detection and Response Readiness

We operationalize telemetry, detection signals, and incident workflows for AI-specific security events.

  • Traceable prompt-plan-tool-action telemetry design
  • AI incident response playbooks and escalation triggers
  • Forensic evidence workflows for customer and governance reporting

Operational Risk Signal

Research-Derived Exposure View Across Bands and Surfaces

Snapshot from our AI risk matrix baseline showing how severity and attack surfaces distribute in the current dataset.

Risk Bands

Critical 13High 21Medium 4
Security16
Reliability8
Compliance5
Privacy5
Safety4

Attack Surfaces

infra5
identity4
model4
prompt4
RAG4
runtime4
tools4
CI-CD3
data3
memory3
Control Mix
PREVENT 18DETECT 6RECOVER 2RESPOND 2

Risk Matrix Explorer

Filter matrix scenarios by risk band, attack surface, and keyword.

38 matching risks
promptCriticalScore 25

Agent Goal Hijack via Prompt Injection

Owner: Platform EngCategory: SecurityMapped Controls: 5Residual: med

OWASP: LLM01:2025 Prompt Injection

MITRE ATLAS: AML.T0051 LLM Prompt Injection

modelCriticalScore 20

Backdoored Model Artifact in Supply Chain

Owner: AppSecCategory: SecurityMapped Controls: 4Residual: high

OWASP: LLM03:2025 Supply Chain

MITRE ATLAS: AML.T0058 Publish Poisoned Models

RAGCriticalScore 20

Credential Harvesting Through Retrieval Content

Owner: Data EngCategory: SecurityMapped Controls: 4Residual: med

OWASP: LLM02:2025 Sensitive Information Disclosure

MITRE ATLAS: AML.T0082 RAG Credential Harvesting

toolsCriticalScore 20

Cross-System Data Exfiltration via Toolchain

Owner: SecOpsCategory: PrivacyMapped Controls: 5Residual: high

OWASP: LLM02:2025 Sensitive Information Disclosure

MITRE ATLAS: AML.T0086 Exfiltration via AI Agent Tool Invocation

memoryCriticalScore 20

Cross-Tenant Memory Leakage

Owner: Platform EngCategory: PrivacyMapped Controls: 4Residual: med

OWASP: LLM02:2025 Sensitive Information Disclosure

MITRE ATLAS: AML.T0085 Data from AI Services

identityCriticalScore 20

Delegated Credential Compromise

Owner: ITCategory: SecurityMapped Controls: 5Residual: med

OWASP: LLM06:2025 Excessive Agency

MITRE ATLAS: AML.T0055 Unsecured Credentials

promptCriticalScore 20

Jailbreak-Driven Policy Bypass

Owner: AppSecCategory: SafetyMapped Controls: 4Residual: med

OWASP: LLM01:2025 Prompt Injection

MITRE ATLAS: AML.T0054 LLM Jailbreak

infraCriticalScore 20

Orchestration Control Plane Exposure

Owner: ITCategory: SecurityMapped Controls: 4Residual: med

OWASP: LLM06:2025 Excessive Agency

MITRE ATLAS: AML.T0075 Cloud Service Discovery

toolsCriticalScore 20

Over-Privileged Tool Invocation

Owner: ITCategory: SecurityMapped Controls: 5Residual: med

OWASP: LLM06:2025 Excessive Agency

MITRE ATLAS: AML.T0053 AI Agent Tool Invocation

identityCriticalScore 20

Privilege Escalation via Role Chaining

Owner: GRCCategory: SecurityMapped Controls: 4Residual: med

OWASP: LLM06:2025 Excessive Agency

MITRE ATLAS: AML.T0012 Valid Accounts

RAGCriticalScore 20

RAG Index Poisoning

Owner: Data EngCategory: SecurityMapped Controls: 4Residual: med

OWASP: LLM04:2025 Data and Model Poisoning

MITRE ATLAS: AML.T0070 RAG Poisoning

runtimeCriticalScore 20

Runaway Autonomous Loop

Owner: Platform EngCategory: SafetyMapped Controls: 4Residual: med

OWASP: LLM06:2025 Excessive Agency

MITRE ATLAS: AML.T0046 Spamming AI System with Chaff Data

Showing first 12 results. Narrow filters to inspect specific scenarios.

Technical Patterns

Engineering Patterns We Apply Across AI Engagements

Policy and Runtime Confinement Patterns

When risk profile requires it, we apply confinement-fabric style controls to enforce deterministic execution boundaries.

Tool and Identity Guardrails

We separate reasoning privileges from action privileges and constrain delegated credentials by policy scope and TTL.

Model, Data, and Supply Chain Controls

We validate model provenance, retrieval trust, and deployment pipeline integrity across CI/CD and artifact paths.

Telemetry, Forensics, and Response Hooks

We design operational telemetry with trace integrity so teams can correlate violations and execute scoped containment.

Methodology References

Our R&D mappings align to common frameworks so leadership, security, and engineering teams can share a consistent risk language.

Start With a Focused AI Security Sprint

We can begin with one high-risk workflow and deliver scoped threat coverage, mitigation priorities, and verification tests your teams can execute immediately.

Threat Modeling
Adversarial Validation
Control Engineering
IR Readiness
Plan AI Security EngagementIncident Response for AI Events