Amazon Details ARTEX AI-Agent Campaigns Targeting AI Credentials and Crypto KYC

Summary
Amazon's MadPot captured ARTEX agent records describing campaigns to harvest AI credentials and bypass crypto-exchange KYC with deepfakes. Amazon could not verify reported activity outside its sensors; recorded KYC attempts were rejected.
Key points
- MadPot sensors posing as LLM inference APIs captured ARTEX agents' task histories from Oct. 3 to Nov. 5, 2026; Amazon says activity outside those sensors could not be verified.
- One campaign's records describe finding exposed AI applications, extracting and validating provider keys, and pooling credentials to power further searches.
- The agents' playbook covered exposed management interfaces, default credentials, unpatched software, SSRF to cloud metadata, and secrets in public code and artifacts.
- A separate campaign's records describe real-time deepfake video and forged identity documents used in attempts to bypass KYC checks at two cryptocurrency exchanges.
- The agents documented a liveness-check sequence and built a deepfake pipeline reaching 11.5 frames per second; the vendor's server-side verdict rejected every recorded attempt.
- Amazon recommends remediating exposed secrets and misconfigurations, applying production controls to AI applications and endpoints, and monitoring for unusual AI-service usage or spend.
Article Details
- Attack Vectors
- Agents searched internet-exposed AI applications and gateways for upstream provider keys, validated discovered credentials, and stored working keys in a managed pool. The article says the agents' records describe this activity; Amazon could not verify reported outcomes.
- The described credential-discovery sources included public code and artifact repositories, package archives, container image layers, notebooks, model-hosting spaces, paste sites, and Telegram channels.
- The agents' records describe testing exposed applications against product-specific attack chains, including uninitialized installations, anonymous management or provider-configuration endpoints, default credentials, and the cited Langflow and RAGFlow vulnerabilities.
- The agents reportedly validated cloud credentials through provider token and identity services, enumerated storage and permissions, and pursued managed AI services, secrets stores, parameter stores, and application identities.
- A separate campaign reportedly used real-time deepfake video and forged identity-document images in attempts to bypass cryptocurrency-exchange KYC checks. The recorded attempts were rejected by the liveness-check vendor's server-side verdict.
- The article reports that campaign instructions required outbound traffic to pass through proxies.
- Defensive Notes
- Remediate default or hardcoded credentials, exposed secrets in code and public artifacts, unauthenticated interfaces and inference endpoints, and unpatched software.
- Treat AI applications, model gateways, and inference endpoints as production systems and apply equivalent security controls.
- Assume exposed secrets and misconfigurations may be discovered quickly; review environments for exposure and remediate promptly.
- Monitor AI services for unexpected spending and unusual usage.
Indicators of compromise
| Type | Indicator | Context |
|---|---|---|
| IPV4 | 103[.]142[.]140[.]158 | Listed in the article's IOC table for Campaign 2. |
| IPV4 | 104[.]28[.]219[.]97 | Listed in the article's IOC table for Campaign 2. |
| IPV4 | 104[.]28[.]225[.]223 | Listed in the article's IOC table for Campaign 1. |
| IPV4 | 104[.]28[.]251[.]98 | Listed in the article's IOC table for Campaign 2. |
| IPV4 | 104[.]28[.]251[.]99 | Listed in the article's IOC table for Campaign 2. |
| IPV4 | 125[.]103[.]213[.]41 | Listed in the article's IOC table for Campaign 2. |
| IPV4 | 128[.]242[.]115[.]131 | Listed in the article's IOC table for Campaign 1. |
| IPV4 | 150[.]136[.]38[.]110 | Listed in the article's IOC table for Campaign 1. |
| IPV4 | 212[.]107[.]28[.]51 | Listed in the article's IOC table for Campaign 2. |
| IPV4 | 216[.]176[.]239[.]231 | Listed in the article's IOC table for Campaign 1. |
| IPV4 | 31[.]22[.]91[.]156 | Listed in the article's IOC table for Campaign 1. |
MITRE ATT&CK
T1078.004 · Cloud AccountsThe records describe validating cloud credentials through provider identity services and pursuing access to cloud resources.T1090 · ProxyCampaign instructions reportedly required all outbound traffic to go through proxies.T1190 · Exploit Public-Facing ApplicationThe agents' vulnerability playbook mapped exposed AI products to attack chains involving management interfaces, default credentials, and known vulnerabilities.T1526 · Cloud Service DiscoveryAfter validating credentials, agents reportedly enumerated managed AI services, secrets and parameter stores, and application identities.T1552.001 · Credentials In FilesThe credential hunt sought secrets left in source code, client-side JavaScript, source maps, debug routes, and environment files.T1593.003 · Code RepositoriesThe described credential hunt searched public code repositories and their event archives for exposed keys.T1595.002 · Vulnerability ScanningThe agents' records describe internet scanning and vulnerability testing against exposed AI applications and gateways.T1619 · Cloud Storage Object DiscoveryThe agents' records describe enumerating storage after obtaining or validating cloud credentials.T1656 · ImpersonationOne campaign reportedly attempted to impersonate identity applicants using real-time deepfake video and forged ID-document images to bypass KYC checks.
CVE
CVE-2025-3248langflow-ai · langflowendpoints, default administrator credentials, such as the LiteLLM default master key, CVE-2025-3248 (Langflow), CVE-2026-28797 (RAGFlow), an authentication bypass via the isCliRequest header in One APICVE-2026-28797infiniflow · ragflowdefault administrator credentials, such as the LiteLLM default master key, CVE-2025-3248 (Langflow), CVE-2026-28797 (RAGFlow), an authentication bypass via the isCliRequest header in One API family systems, SSRF
Vendors
Products
DifyTargets included LLM gateways and proxy platforms such as One API, New API, Veloera, Sub2API, and LiteLLM, and AI application builders such as Dify, FastGPT, Langflow, RAGFlow, Open WebUI, LobeChat, and Ollama.FastGPTTargets included LLM gateways and proxy platforms such as One API, New API, Veloera, Sub2API, and LiteLLM, and AI application builders such as Dify, FastGPT, Langflow, RAGFlow, Open WebUI, LobeChat, and Ollama.LangflowTargets included LLM gateways and proxy platforms such as One API, New API, Veloera, Sub2API, and LiteLLM, and AI application builders such as Dify, FastGPT, Langflow, RAGFlow, Open WebUI, LobeChat, and Ollama.LiteLLMTargets included LLM gateways and proxy platforms such as One API, New API, Veloera, Sub2API, and LiteLLM, and AI application builders such as Dify, FastGPT, Langflow, RAGFlow, Open WebUI, LobeChat, and Ollama.New APITargets included LLM gateways and proxy platforms such as One API, New API, Veloera, Sub2API, and LiteLLM, and AI application builders such as Dify, FastGPT, Langflow, RAGFlow, Open WebUI, LobeChat, and Ollama.One APITargets included LLM gateways and proxy platforms such as One API, New API, Veloera, Sub2API, and LiteLLM, and AI application builders such as Dify, FastGPT, Langflow, RAGFlow, Open WebUI, LobeChat, and Ollama.Open WebUITargets included LLM gateways and proxy platforms such as One API, New API, Veloera, Sub2API, and LiteLLM, and AI application builders such as Dify, FastGPT, Langflow, RAGFlow, Open WebUI, LobeChat, and Ollama.RAGFlowTargets included LLM gateways and proxy platforms such as One API, New API, Veloera, Sub2API, and LiteLLM, and AI application builders such as Dify, FastGPT, Langflow, RAGFlow, Open WebUI, LobeChat, and Ollama.Sub2APITargets included LLM gateways and proxy platforms such as One API, New API, Veloera, Sub2API, and LiteLLM, and AI application builders such as Dify, FastGPT, Langflow, RAGFlow, Open WebUI, LobeChat, and Ollama.VeloeraTargets included LLM gateways and proxy platforms such as One API, New API, Veloera, Sub2API, and LiteLLM, and AI application builders such as Dify, FastGPT, Langflow, RAGFlow, Open WebUI, LobeChat, and Ollama.
Tools
ARTEXrequests from AI agents that included operating memory from offensive campaigns that threat actors ran on ARTEX, an open-source agentic AI penetration testing framework.MadPot5, 2026, Amazon’s MadPot, a globally distributed network of decoy threat sensors, captured requests from AI agents that included operating memory from offensive campaigns that threat actors ran on ARTEX, an open-source
