Inkog vs Semgrep

Semgrep is a generic SAST tool. Inkog is purpose-built for AI agents.

The Difference

Aspect	Semgrep	Inkog
Focus	All code vulnerabilities	AI agent behavioral flaws
Detection	Pattern matching on AST	Semantic analysis + taint tracking
Understands	Code syntax	Agent loops, tool chains, LLM flows
Frameworks	None (generic)	16 AI frameworks natively
Compliance	Generic CWE	EU AI Act, OWASP LLM, NIST AI RMF

What Semgrep Catches


# Semgrep rule: python.lang.security.audit.dangerous-subprocess-use
subprocess.run(user_input, shell=True)  # ✓ Detected

Semgrep finds this because it matches the pattern subprocess.run(..., shell=True).

What Semgrep Misses


# Agent loop without termination
while llm.should_continue():
    result = llm.invoke(prompt)
    prompt = result  # Feedback loop
 
# Semgrep: No finding (not a known pattern)
# Inkog: CRITICAL - Infinite loop detected

Semgrep doesn’t understand that this is an agent loop. Inkog’s Universal IR recognizes the LoopNode → LLMCallNode → feedback pattern.

Real Example


from langchain.agents import AgentExecutor
 
agent = AgentExecutor(
    agent=react_agent,
    tools=tools,
    # No max_iterations
)

Tool	Finding
Semgrep	Nothing
Inkog	`CRITICAL: AgentExecutor without iteration limit (infinite loop risk)`

When to Use Each

Use Semgrep for:

SQL injection in web apps
XSS in templates
Generic code quality
Custom rules for your codebase

Use Inkog for:

AI agent security
LLM application vulnerabilities
Compliance (EU AI Act, OWASP LLM)
Multi-agent systems

Use Both

They’re complementary. Run Semgrep for traditional vulnerabilities, Inkog for AI-specific issues:


# .github/workflows/security.yml
jobs:
  security:
    steps:
      - uses: returntocorp/semgrep-action@v1
      - uses: inkog-io/inkog-action@v1

Bottom Line

Semgrep is excellent for general SAST. It has no AI agent awareness.

Inkog understands agent loops, tool chains, prompt flows, and multi-agent delegation. It maps to AI-specific compliance frameworks.

Different tools, different jobs.