Exogram vs Rebuff AI
“Prompt injection detection. Same execution gap.”
Executive Architecture Matrix
Side-by-side technical capability breakdown between Rebuff AI and Exogram.
| Technical Dimension | Rebuff AI | Exogram Authority Runtime |
|---|---|---|
| Threat Model | Adversarial inputs | All tool calls (adversarial or not) |
| Non-Injected Threats | Not covered | Fully covered |
Execution Failure Containment
How unexpected autonomous errors, injection payloads, and runaway cycles are intercepted in live production.
SQL & Data Mutations
Rebuff AI relies on natural language alignment or connection permissions. Unsanitized mutations execute against target databases.
Intercepts the SQL AST in 0.07ms, enforcing strict read-only constraints and table mutation barriers.
Rogue API & Retry Loops
Agents can enter cyclical retry states upon receiving error responses, firing thousands of unauthorized tool calls.
Tracks state transitions across turns, halting infinite loops and duplicate mutations on turn 2.
Memory Drift & Poisoning
Context windows accumulate hallucinations and conflicting state over long-horizon sessions.
Maintains SHA-256 state hashing across all memory writes, verifying facts before persistence.
Latency & Compute Footprint
Deterministic CPU execution eliminates secondary LLM inference delays and API billing.
Dependent on secondary model API hops, token generation, or cloud roundtrips.
Compiled deterministic bitmask logic gates running on standard host CPU.
Exogram evaluates actions inside your application process in 0.07ms with zero network hops and zero recurring token costs.
Real-World Production Scenario
Concrete breakdown of an autonomous agent failure mode in live production.
Un-Gated Action Execution vs. Governed Autonomy Interception
Without Exogram Protection
With Exogram Interception
The Plain English Verdict
Use Rebuff for injection detection. Use Exogram because the model can generate harmful actions without being injected.
Prompt Injection Defense: Why LLM-as-a-Judge Fails in Production
Using a probabilistic model to police another probabilistic model introduces latency, non-determinism, and compounding attack surfaces. Execution boundaries must be evaluated in compiled code.
What Rebuff AI Does
- •Rebuff detects prompt injection using heuristic, LLM-based, and vector similarity methods.
- •Open-source. Multi-method detection for catching adversarial inputs.
- •Stops injected prompts. Does not stop harmful actions from non-injected prompts.
What Exogram Does
- Exogram operates downstream from injection. Even clean prompts can produce dangerous tool calls.
- The model can hallucinate, invent parameters, and propose mutations without any injection.
- Exogram catches what injection defense misses: the model's own errors.
Is Rebuff AI vulnerable to execution drift?
Run a static analysis on your agent tool-calling pipeline below.
Frequently Asked Questions
Is prompt injection the only threat to AI agents?
No. Models hallucinate schemas, invent parameters, drift constraints, and propose destructive mutations — all without any injection. Exogram covers the full threat surface.