APromptRiskDBThreat intelligence atlas
AI Security Technique

Software Tools - AI Security Technique

Adversaries may search for and obtain software tools to support their operations. Software designed for legitimate use may be repurposed by an adversary for malicious intent. An adversary may modify or customize software tools to achieve their purpose. Software tools used to support attacks on AI systems are not necessarily AI-based themselves.

AI Security Techniquerealized

Record summary

A quick snapshot of what this page covers.

Tactics0Attacker goals connected to this method.
Mitigations0Defenses that may help against this attack.
AI risks0Research-backed risks connected to this topic.

Attack context

How this AI attack works in practice.

ATLAS ID
AML.T0016.001
ATT&CK external ID
T1588.002
Priority score
60
Maturity: realized

Mitigations

Defenses that may help against this attack.

No connected defenses. No defense is connected to this attack in the current data.

Case studies

Examples from public reports and exercises.

Live Deepfake Image Injection to Evade Mobile KYC Verification

exercise
Date2024-10-01

Facial biometric authentication services are commonly used by mobile applications for user onboarding, authentication, and identity verification for KYC requirements. The iProov Red Team demonstrated a face-swapped imagery injection attack that can successfully evade live facial recognition authentication models along with both passive and active liveness verification on mobile devices. By executing this kind of attack, adversaries could gain access to privileged systems of a victim or create fake personas to create fake accounts on banking or cryptocurrency apps.

LLM Jacking

incident
Date2024-05-06

The Sysdig Threat Research Team discovered that malicious actors utilized stolen credentials to gain access to cloud-hosted large language models (LLMs). The actors covertly gathered information about which models were enabled on the cloud service and created a reverse proxy for LLMs that would allow them to provide model access to cybercriminals.

The Sysdig researchers identified tools used by the unknown actors that could target a broad range of cloud services including AI21 Labs, Anthropic, AWS Bedrock, Azure, ElevenLabs, MakerSuite, Mistral, OpenAI, OpenRouter, and GCP Vertex AI. Their technical analysis represented in the procedure below looked at at Amazon CloudTrail logs from the Amazon Bedrock service.

The Sysdig researchers estimated that the worst-case financial harm for the unauthorized use of a single Claude 2.x model could be up to $46,000 a day.

Update as of April 2025: This attack is ongoing and evolving. This case study only covers the initial reporting from Sysdig.

Camera Hijack Attack on Facial Recognition System

incident
Date2020-01-01

This type of camera hijack attack can evade the traditional live facial recognition authentication model and enable access to privileged systems and victim impersonation.

Two individuals in China used this attack to gain access to the local government's tax system. They created a fake shell company and sent invoices via tax system to supposed clients. The individuals started this scheme in 2018 and were able to fraudulently collect $77 million.

Source

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