All software is vulnerable to supply chain attacks, but I believe AI is particularly vulnerable. Let me explain why.

• Let me begin by firstly explaining what a supply chain attack is in regular software development.
• A software supply chain attack is a type of cyberattack that targets an organization by compromising the less-secure elements - or "links" - within the trusted process of developing, building, distributing, or updating software.
• Instead of attacking the final target directly, the attacker infiltrates a third-party vendor or a component that the target organization uses.
• The goal is to secretly inject malicious code into a legitimate product or update that is then delivered to a wide range of unsuspecting customers. Because the compromised software comes from a trusted, official source, it typically bypasses the target's existing security defences.
• This type of attack is particularly dangerous because modern software development relies heavily on external components and tools, such as open-source code libraries, vendor-supplied applications, and automated build systems (CI/CD pipelines).
• Threat actors exploit this complexity by introducing a flaw at any stage before the software reaches the end-user.
• This could involve modifying the original source code, replacing a legitimate dependency with a malicious one (a technique known as "dependency confusion"), or compromising the vendor's update server to push a tainted patch.
• Once the compromised software is deployed by the customer, the malicious code executes, giving the attacker a backdoor into the victim's network.
• A high-profile example is the SolarWinds attack that was discovered in late 2020.
• SolarWinds is an IT management company whose Orion platform is widely used by thousands of private companies and government agencies to monitor their networks.
• Attackers managed to compromise SolarWinds' software build environment and inserted a backdoor, called SUNBURST, into a seemingly routine and legitimate software update for the Orion platform.
• When SolarWinds customers downloaded and installed this trusted update, they unknowingly executed the malicious code.
• The SUNBURST backdoor lay dormant for a period before becoming active and providing the attackers with remote access and control over the compromised networks.
• This attack successfully leveraged the implicit trust between a software vendor and its customers to achieve a massive, far-reaching breach against highly-secured organizations.
• Another infamous supply chain attacked was performed against CrowdStrike in 2024, I covered that attack in more detail in a previous episode here: https://techleader.pro/a/654-The-CrowdStrike-outage-(TLP-2024w29)
• But what about AI?
• AI platforms that source training data from the internet are highly vulnerable to supply chain attacks, primarily through the technique known as data poisoning.
• The AI supply chain isn't just the code; it includes the vast collection of training data, the algorithms, the open-source libraries, and the pre-trained models used by developers.
• When an AI platform relies on data scraped from the open internet, it essentially accepts inputs from an untrusted, external source, making the data the weakest link in the chain.
• The primary way an attack occurs is through Data Poisoning:
  • Malicious Injection: Attackers can inject poisoned data into publicly accessible repositories or large, uncurated internet sources (like social media, forums, or specific file-sharing sites) that AI platforms are known to scrape for training.
  • Corrupting the Model's Integrity: When the AI model (like a large language model or image generator) is trained on this compromised data, it learns the incorrect, biased, or malicious patterns the attacker intended. This corruption is baked directly into the final model's "knowledge" or weights.
  • The Backdoor Trigger: Often, the goal isn't to completely break the model, but to implant a hidden backdoor. This is a specific, subtle "trigger" (like a unique phrase, token, or pattern) that the model learns to associate with a targeted, malicious output. The model will behave normally until an attacker uses the trigger, at which point the model will execute the secret, harmful instruction (e.g., generate misinformation, bypass safety filters, or output malicious code).
• This isn't just a theoretical threat; techniques have been demonstrated in the real world, for example:
  • Model Jailbreaking via Training Data: Attackers have posted specific jailbreak prompts onto public forums and social media that were later ingested by large language models (LLMs). Once deployed, a user simply typing that phrase could cause the model to bypass its ethical and safety guardrails, essentially activating the backdoor planted through the training data.
  • Nightshade Tool: This tool was created to allow artists to subtly alter the pixels in their images before uploading them online. When a generative AI model scrapes these "poisoned" images, it learns to misclassify objects or generate distorted output when prompted with similar images, intentionally degrading the model's accuracy and reliability.
• This is a supply chain attack because the attacker targets a third-party component (the raw data supply from the internet) to compromise the final product (the deployed AI model) without having to directly breach the AI platform's internal network or code.
• So long as we train AI models from internet data, they will remain vulnerable to a poisoned well of data.

Sources:

SolarWinds hack explained: Everything you need to know - https://www.techtarget.com/whatis/feature/SolarWinds-hack-explained-Everything-you-need-to-know

SolarWinds Sunburst Cyberattack: Targeting the software industry supply chain in history - https://delinea.com/blog/solarwinds-sunburst-supply-chain-cyber-attack-software-industry

Investigating LLM Jailbreaking of Popular Generative AI Web Products - https://unit42.paloaltonetworks.com/jailbreaking-generative-ai-web-products/

What is Nightshade – the new tool allowing artists to ‘poison’ AI models? - https://www.weforum.org/stories/2023/11/nightshade-generative-ai-poison/

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