Like many others, I recently read the Anthropic misuse report and the subsequent Reuters coverage. Both confirm something security leaders have anticipated but hoped we wouldn’t see so soon: attackers are now feeding malware into AI frameworks to improve it.
And they’re not doing it by uploading raw executable files. AI platforms already block those. Instead, they’re embedding malware inside the very same everyday productivity files that AI systems accept for legitimate work such as:
- PDFs
- Word documents
- Spreadsheets
- Logs
- ZIP archives
- Source code files
- Images with metadata
In my upcoming book, Cybersecurity Upside Down, I discuss why these formats have always been the most reliable malware carriers. That hasn’t changed. What has changed is that AI frameworks now ingest these files directly, interpret them as content, and critically attempt to help. Attackers simply ask the model to fix errors, adjust logic, or generate new variants. The AI becomes an unwitting malware development assistant.
Neutral public examples how common and trusted file types routinely deliver malware:
Once a file passes basic upload filters, the AI reads the content as text rather than a threat. AI frameworks trust the file format. Attackers exploit that trust. And that makes this attack path both subtle and effective.
This is exactly where Deep Content Disarm and Reconstruction (Deep CDR) becomes not just useful – but completely necessary.
What Deep CDR Actually Does
DEEP CDR is fundamentally different from traditional detection technologies. It does not rely on signatures, heuristics, or behavioral analysis. It does not try to inspect files to decide whether a file might be safe.
Instead, Deep CDR begins with one simple assumption: any file could be malicious.
Its strength comes from a three-stage process:
- Identify the true file type
Deep CDR inspects the internal structure of the file. If the file is disguised as something else, Deep CDR identifies what it really is and blocks or processes it appropriately. - Unpack the file completely
Deep CDR opens the file… then opens any objects embedded inside it… then unpacks archives inside those… continuing until every layer is exposed. Nothing remains hidden. - Regenerate a clean, safe version of the file
This is the important part. Deep CDR does not “clean” the original file. It constructs a brand-new PDF, Word document, spreadsheet, or image using only the safe, valid content – removing scripts, macros, embedded logic, and any hidden components.
The output looks the same to the user, but the dangerous code never reaches the AI system in the first place.
Why Every AI Workflow Needs DEEP CDR
Any AI system that accepts user-uploaded files is exposed to file-based threats. Productivity files still remain the number one malware vector, and that is not going to change. AI adoption has dramatically increased the volume of files being processed. That scale amplifies the risk.
AI models are built to read and interpret content, not to analyze the structure in the file for malicious behavior. They do not inspect embedded code or hidden components. They simply process whatever is inside.
Deep CDR closes this gap. It ensures that before the AI ever processes a file, the file has already been fully reconstructed into a safe, trusted version. It protects the AI system, the user, and the organization deploying it.
Explore how Deep CDR works here.
