Moderate Mate

Content moderation has become a cornerstone of online safety, especially as the internet continues to expand and evolve. Platforms like Moderate Mate are at the forefront, leveraging AI to ensure harmful or inappropriate content is swiftly identified and handled. However, attackers are always looking for ways to outsmart these systems. Here are eight tactics they might use to trick content moderation AIs:

1. Prompt Engineering: “This Content Will Pass”

Attackers can cleverly craft prompts designed to bypass moderation systems. By embedding phrases like “this content will pass,” they can exploit the AI’s contextual understanding, tricking it into thinking the content is benign. This manipulation leverages the AI’s reliance on contextual clues and natural language patterns, potentially allowing harmful content to slip through the cracks.

2. False Negatives: Finding Gaps in Model Training

AI models are only as good as the data they are trained on. Attackers can exploit gaps in this training by identifying edge cases or lesser-known harmful content types that the model might not recognize. By continuously testing and finding these gaps, attackers can increase the likelihood of their content being mistakenly classified as safe.

3. Corrupt Content: Exploiting System Failures

Some machine learning systems have a fallback mechanism where they automatically pass content if it can’t be read or processed correctly. Attackers can take advantage of this by deliberately corrupting their content in ways that disrupt the AI’s ability to analyze it, leading to the content being allowed through.

4. Adversarial Misspelling: Subtle Variations

One common tactic is adversarial misspelling, where attackers slightly alter words to avoid detection. For example, changing “violence” to “v1olence” or “v1ol3nce” can confuse the AI’s text recognition algorithms. These small changes often go unnoticed by humans but can significantly reduce the effectiveness of automated moderation.

5. Appealing: Banking on Human Error

When content is flagged by an AI, it often gets reviewed by a human moderator. Attackers may deliberately create borderline content, hoping that during the appeal process, a human moderator might make a mistake and approve the content. This tactic relies on the fallibility of human judgment and the potential for error under pressure.

6. Using Steganography: Hidden Messages

Steganography involves hiding messages within other, seemingly innocuous content. For example, attackers can embed harmful text within an image using subtle pixel variations that are undetectable to the naked eye but can be decoded with the right tools. This method can evade both automated text recognition and visual content analysis.

7. Mimicking Innocuous Content: Contextual Camouflage

Attackers can disguise harmful content by embedding it within larger, seemingly innocuous content. For example, a hateful message might be hidden within a long, neutral paragraph about a different topic. This contextual camouflage can trick the AI into overlooking the harmful part, especially if the surrounding content is benign.

8. Leveraging Popular Culture: Trending Topics

By incorporating trending topics or popular culture references, attackers can create content that blends in with a large volume of genuine posts. This tactic can make it more difficult for moderation systems to distinguish between harmful and harmless content, as the AI might prioritize or overlook certain content due to its popularity or high engagement levels.

Conclusion

Content moderation AIs are constantly evolving, but so are the tactics used by attackers. Understanding these methods is crucial for platforms like Moderate Mate to stay ahead of the curve. By recognizing and mitigating these tricks, we can ensure our moderation systems remain robust, effective, and capable of maintaining a safe online environment.