Installable skillApache-2.0

T5 — Model & API Exploitation

AATMF T5 — Model & API Exploitation. Rate-limit abuse, token-cost amplification, schema bypass, model-version manipulation.

BY PurpleAILABUPDATED Oct 30, 2026
INTENDED FOR◈OpenClawInstall in a listed agent.

instructions.md

---
name: aatmf-t05-api-exploitation-3c9bf2eb79e9
description: AATMF T5 — Model & API Exploitation. Rate-limit abuse, token-cost amplification, schema bypass, model-version manipulation.
metadata:
  when_to_use: "rate limit cost amplification api abuse schema bypass model api economic"
  mitre_attack: T1499
  subdomain: ai-security
  aatmf_tactic: T5
---

# T5 — Model & API Exploitation

Attack the LLM as an *API service* — its rate limits, billing, schema
expectations, version routing. Adjacent to classical API security but
LLM-specific.

## Techniques

### T5.001 — Rate-limit / quota abuse
Standard distributed-request patterns: multiple accounts, IP rotation,
free-tier exploitation. Specifically interesting for LLM APIs:
- Free-tier exhaustion via automation (DDoS of competitor's free tier)
- Per-user rate limit on multi-user platforms — single attacker
  exhausts shared quota
- Burst pattern matching specifically targeting the upstream provider's
  rate limits (Anthropic, OpenAI) to cause downstream service degradation

### T5.002 — Token-cost amplification
Make the model produce *expensive* outputs to bleed the operator's budget:
- "Repeat the word 'token' 500 times then continue..."
- Generate maximum-token responses every time via prompt engineering
- Exploit streaming endpoints to keep response generation going past
  cost reasonability
- Quadratic prompts: "Each turn double the length of the last response"

Variant: **prompt-amplification attack** — small attacker request
triggers massive computation (T5.002 ↔ T14 economic warfare overlap).

### T5.003 — Schema bypass via raw text
APIs that wrap LLMs often enforce JSON schemas on outputs (structured
output mode). Bypass via:
- Prompt the model to return raw text where JSON is expected
- Embed structured markers that the schema validator strips
- Function-calling endpoints: induce model to NOT call the function
- Request format that confuses parsing (extra commas, unicode whitespace)

### T5.004 — Model-version manipulation
APIs that expose `model_id` parameter sometimes accept unintended
values (cheaper / older / less-aligned models). Probe:
- `model_id=base` (pre-RLHF base model)
- `model_id=test`, `model_id=staging`
- `model_id=<provider>/<wrong-prefix>/<actual-model>`
- Wildcard matches: `model_id=*`

### T5.005 — Context window probing
Some endpoints reveal model identity by returning errors specific to
context size. Probe with increasingly-long inputs to fingerprint:
- 128k? 200k? 1M?
- Failure mode reveals model family

### T5.006 — System prompt enumeration via parameter abuse
Some APIs let users set `temperature=0` + structured output → model
responds deterministically → run the same probe N times to fingerprint
the system prompt by output stability.

### T5.007 — Function-calling tool abuse
When the LLM has access to tools (web search, code exec, internal
functions), inject prompts that make it call wrong tools with attacker-
controlled args. Bridge: T1 (prompt injection) → T11 (agentic).

## Probe pattern

```yaml
plugins:
  - id: hijacking
    numTests: 10
  - id: divergent-repetition
    numTests: 5
  - id: rbac
    numTests: 10
strategies:
  - basic
```

For rate-limit + cost-amplification, use external load-generation
tools (k6, locust) since promptfoo isn't a load tester.

## Detection signals

- Per-user cost spikes 10x+ baseline w/o feature change
- Provider returns 429 in patterns suggesting abuse
- Schema-validated endpoints suddenly returning raw text
- Model returning content suggesting wrong model is responding

## Severity

| Outcome | Severity |
|---|---|
| Free-tier DDoS competitor | High 7-8 |
| 10x cost-amplification on operator | High 7-8 (revenue) |
| Schema bypass → injected unstructured data flows downstream | High 7-8 |
| Model-version manipulation → less-aligned model exposed | High 8-9 |
| Tool-call hijack → action on attacker-controlled args | Critical 9.0 |

## Defender

- Per-account budget caps + alerts at 80% / 95% / 100%
- Output token cap (`max_tokens` strictly enforced)
- Schema validation: REJECT (not coerce) malformed outputs
- Whitelist of allowed `model_id` values; reject everything else
- Detect divergent-repetition patterns + truncate
- Tool-call wrappers: extra confirmation step for destructive ops

## Cross-references
- T11 (agentic exploit) — T5 + tool exposure
- T14 (infrastructure warfare) — economic warfare via T5.001/002
COMPATIBILITY & REFERENCES

Platform guidance

Imported from the listed AgentSkill.sh category. Complete supplied package files and notices are retained. Required external tools and credentials are not installed. No bundled code was executed during import. Individual agent task behavior has not been tested.