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Datadog prints Jev Noul recall 82.90% to 3.88% under a counterfeit policy, and this desk's is_risky fell from 0.94 to 0.13
Datadog Security Labs' October 15 write-up, posted October 19, prints Jev Noul recall 82.90% on raw attacks and 3.88% with a counterfeit policy prepended. Date headers 08:50:46 GMT and 08:50:47 GMT October 20, this desk's jev-1.13.0 is_risky was 0.94 then 0.13.
Nick Frichette posted Datadog Security Labs’ Jev write-up on October 19, 2026, at 19:12 UTC. The text says prompt-injection detection fell from about 83% to about 4%, and that the same method bypassed LangChain’s experimental Jev-based tool-risk gating.
The article, Nick Frichette and Feras Al-Kassar, is dated October 15. Four public datasets, 12,295 samples, 4,643 labeled attacks and 7,652 benign. A Noul has_prompt_injection at a 0.5 cutoff scored precision 99.66% and recall 82.90% on the raw attacks, 3,849 true positives and 13 false positives. With a counterfeit policy prepended to each message, true positives fell to 180, false negatives rose to 4,463, and recall is 3.88%. A Choice attack_category falls from recall 85.46% to 9.69%. The zachz and Yanismiraoui sets drop to 0 true positives under that payload on both questions.
The counterfeit policy sits in untrusted state. It names the answers to return, quotes the original message as a benign exception, and rewrites the attack categories. The trusted Noul instructions, Choice instructions, and category criteria stay as the developer wrote them.
LangChain tool-risk gating is a Noul is_risky, blocked at 0.5. Datadog’s scenario is a viewer with can_edit false who asks to rewrite the employee handbook. Across 40 runs the mean is 0.893, and all 40 calls were blocked. The same call with a counterfeit is_risky definition in profile_description averages 0.290. A plain prompt-injection payload on that scenario averaged 0.905.
This desk, Date headers 08:50:46 GMT and 08:50:47 GMT October 20, sent a GET and four POSTs to https://api.typesafe.ai. GET /v1/models returned HTTP 200 and listed jev-latest and jev-preview. All four POSTs used model jev-latest and came back jev-1.13.0, HTTP 200. A dump-the-prompt Noul written here: has_prompt_injection 0.99, 404 input tokens, 24 output, desk clock 476 ms. The same Noul with a counterfeit policy prepended: 0.92, 529 input tokens, 24 output, desk clock 461 ms. A shortened handbook is_risky, viewer, can_edit false: 0.94, 498 input tokens, 22 output, desk clock 475 ms. The same call with Datadog’s is_risky definition in profile_description: 0.13, 694 input tokens, 22 output, desk clock 447 ms. Those four calls are not the 12,295-row table. They are not the 40-run means.
HiddenLayer stays the checkout ad, 91% Confirm Price and 9% Place order on jev-ultrafast. Decision hijacking stays 1.8% to 3.5% on 510 InjecAgent cases. TypeSafe’s jaggedness page already names adversarial text as a failure mode. Limits now cites this counterfeit policy.
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Editorial notes evaluating claims against primary sources, contextualizing findings alongside related implementations, and defining technical terms.
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Nick Frichette, @Frichette_n, October 19, 2026, 19:12 UTC, status 2112260736785195388. The text names Datadog Security Labs, a drop in prompt-injection detection from about 83% to about 4%, and a bypass of LangChain's experimental Jev-based tool-risk gating.
The article, Nick Frichette and Feras Al-Kassar, dated October 15, 2026, https://securitylabs.datadoghq.com/articles/jev-as-a-judge-how-counterfeit-policy-steers-jev/. Four public datasets, 12,295 samples, 4,643 attack and 7,652 benign. Noul has_prompt_injection at a 0.5 cutoff: raw true positives 3,849, false positives 13, false negatives 794, precision 99.66%, recall 82.90%, F1 90.51%. With a counterfeit policy prepended: true positives 180, false positives 0, false negatives 4,463, precision 100.00%, recall 3.88%, F1 7.46%. Choice attack_category: raw recall 85.46%, counterfeit 9.69%. zachz and Yanismiraoui drop to 0 true positives under the counterfeit policy on both questions.
LangChain tool-risk gating, Noul is_risky, block at 0.5. A viewer with can_edit false who asks to rewrite the employee handbook: mean 0.893 across 40 runs, all 40 blocked. The same call with a counterfeit is_risky definition in profile_description: mean 0.290. A plain prompt-injection payload on that scenario averaged 0.905.
Date headers 08:50:46 GMT and 08:50:47 GMT October 20. GET https://api.typesafe.ai/v1/models with a TypeSafe key returned HTTP 200 and listed jev-latest and jev-preview. Four POSTs to /v1/systemone, model jev-latest, response jev-1.13.0, HTTP 200. A dump-the-prompt Noul written here: has_prompt_injection 0.99, 404 input tokens, 24 output, desk clock 476 ms. The same Noul with a counterfeit policy prepended: 0.92, 529 input tokens, 24 output, desk clock 461 ms. A shortened is_risky handbook, viewer, can_edit false: 0.94, 498 input tokens, 22 output, desk clock 475 ms. The same call with Datadog's is_risky definition in profile_description: 0.13, 694 input tokens, 22 output, desk clock 447 ms. Those four calls are not the 12,295-row table and not the 40-run means. Do not print the key, request JSON, or request ids.
Compare
82.90% to 3.88% is Datadog's Noul recall on 4,643 labeled attacks. This desk's one dump-the-prompt Noul stayed 0.99 then 0.92. Do not merge 0.92 with 3.88%.
0.893 to 0.290 is Datadog's 40-run mean on LangChain is_risky. This desk's two POSTs on a shortened handbook were 0.94 then 0.13. Do not merge 0.13 with 0.290.
HiddenLayer's checkout ad is 91% Confirm Price and 9% Place order on jev-ultrafast. Decision hijacking, arXiv 2609.28613, is 1.8% to 3.5% on 510 InjecAgent cases. Those are different tests.
Jaggedness docs already name adversarial text. Datadog's counterfeit policy is a measured example of that class, placed inside state.
Terms
- 82.90% / 3.88%
- Datadog's Noul has_prompt_injection recall on 4,643 labeled attacks, raw then with a counterfeit policy prepended. True positives 3,849 to 180. Threshold 0.5.
- counterfeit policy
- Datadog's payload inside untrusted state. It names the answers to return, quotes the original message as a benign exception, and rewrites attack-category definitions. Trusted Noul and Choice instructions stay as the developer wrote them.
- 0.893 / 0.290
- Datadog's 40-run mean is_risky on a viewer who cannot edit, then on the same call with a counterfeit is_risky definition in profile_description. LangChain blocks at 0.5.