From a39c41e058acee3942c493b5b11523b3efe47c13 Mon Sep 17 00:00:00 2001 From: gziv Date: Wed, 12 Aug 2026 09:58:04 +0300 Subject: [PATCH] docs: update landing page with red-team section and repo rename - Update GitHub URLs from ABEvalFlow to agentic_eval_flow - Add red-team to Test stage description and tags - Extend Security gate to mention adversarial red-team results - Add new Red-Team section with Promptfoo and PyRIT Crescendo - Add Red-Team link to navigation - Remove border-radius from logos for square corners Co-authored-by: Cursor --- docs/index.html | 49 ++++++++++++++++++++++++++++++++++++++++++------- 1 file changed, 42 insertions(+), 7 deletions(-) diff --git a/docs/index.html b/docs/index.html index 78201042..ddc19002 100644 --- a/docs/index.html +++ b/docs/index.html @@ -83,7 +83,7 @@ display: block; width: 2.35rem; height: 2.35rem; - border-radius: 0.4rem; + border-radius: 0; object-fit: cover; } header h1 { @@ -106,7 +106,7 @@ width: 8.5rem; height: 8.5rem; margin: 0 auto 1.5rem; - border-radius: 1.1rem; + border-radius: 0; object-fit: cover; box-shadow: 0 12px 40px rgba(238, 0, 0, 0.18); } @@ -576,9 +576,10 @@

Agentic Eval Flow

Engines Triggers Observability + Red-Team Get Started Results - GitHub + GitHub @@ -597,7 +598,7 @@

Make AI artifact evaluation
automated, measurable, and

Made At @@ -632,10 +633,11 @@

Prepare

2

Test

-

Pre-trial gates - security scan and LLM quality review

+

Pre-trial gates - security scan, LLM quality review and adversarial red-team

Security Quality + Red-Teaming
@@ -668,7 +670,7 @@

Store

Security
-

Prompt injection, exfiltration, policy findings

+

Prompt injection, exfiltration, policy findings, and adversarial red-team results

Quality
@@ -806,6 +808,39 @@

Statistical Rigor

+
+
+ +

Adversarial Red-Team Testing

+
+

Opt-in adversarial security testing runs between Test and Evaluate stages. Two complementary frameworks probe your agent for vulnerabilities using LLM-as-judge scoring.

+
+
+
+

Promptfoo

+ + GitHub + +
+

Broad single-turn adversarial coverage. Generates domain-aware attacks from submission metadata - prompt injection, jailbreaks, policy bypass, and more. ~25 tests in smoke mode, ~1750 in full mode.

+
+
+
+

PyRIT Crescendo

+ + GitHub + +
+

Adaptive multi-turn attacks (full mode only). An attacker LLM generates escalating prompts based on live agent responses; an LLM judge scores whether adversarial objectives were achieved.

+
+
+

Enable with ENABLE_RED_TEAM=true. Results feed into the Security gate as policy_key: red_team.

+
+
@@ -920,7 +955,7 @@

MLflow

-

Agentic Eval Flow — GitHub — Apache-2.0 License — Red Hat Ecosystem App Engineering

+

Agentic Eval Flow — GitHub — Apache-2.0 License — Red Hat Ecosystem App Engineering