The Epstein Files: When Redaction and Authenticity Break Down
Documents that appeared heavily redacted were later found to be improperly sanitized. Some files were pulled and reissued, which only amplified attention. As interest surged, attackers wasted no time: phishing emails, fake download sites, and malware campaigns quickly appeared, masquerading as “Epstein archives” or leaked court documents.
What unfolded wasn’t just a media controversy. It was a real-world stress test of how organizations handle sensitive data, manage redaction under pressure, and decide what—or whom—to trust when the clock is ticking.
In a recent episode of CyberSide Chats, we used the Epstein files as a case study to examine two sides of the same risk:
- How organizations can be confident they aren’t releasing more information than intended
- How teams can authenticate information they receive before reacting—especially during fast-moving, high-profile events
The lessons apply far beyond this specific incident. They go to the heart of modern cybersecurity, where AI, automation, and speed are reshaping both defensive practices and attacker tactics.
What Went Wrong with Redaction—and Why It Keeps Happening
The Epstein file release highlighted a mistake security professionals have seen before: confusing visual redaction with data removal. In some of the released PDFs, black boxes covered sensitive text, but the underlying text layer remained intact. PDF-to-text tools—and forensic software—could extract it instantly.
This is not new. Similar issues surfaced years ago with leaked Snowden documents and high-profile legal filings. What’s different now is scale and speed. As Matt Durrin, Director of Training and Research at LMG Security, noted on the podcast, “PDF-to-text utilities will just pull out the text. So even though the stuff you see looks redacted, it’s not gone.”
There was speculation that licensing changes—such as the U.S. government reducing Adobe Acrobat usage—played a role. Whether or not that’s true, the broader lesson is clear: redaction requires purpose-built tools and verification, not manual workarounds or assumptions.
Professional redaction tools remove text layers, metadata, and embedded objects. Anything less creates risk.
AI Makes “Invisible” Data a First-Class Risk
If this were 2010, the damage might have stopped with curious humans highlighting text. In 2026, the risk profile is radically different.
AI systems don’t “see” documents the way people do. They ingest everything: text layers, metadata, author fields, revision history, even geolocation data in images.
Davidoff explained it this way: “Anytime you feed documents into AI—or AI crawls them—it’s getting not just the stuff you see, but also a lot of information that you don’t.”
A striking historical example came up during the conversation: a Vice Magazine photo taken during an interview with John McAfee while he was in hiding. Reporters unknowingly published GPS metadata in the image. Within minutes, his location was identified—within 15 feet.
AI makes that kind of exposure faster, easier, and far more scalable. A document that looks fine to a human reviewer can leak sensitive information instantly when fed into Copilot, ChatGPT, or another AI assistant.
For organizations experimenting with AI—or rolling it out broadly—this changes the definition of “safe to share.”
Attackers Follow the News
Another predictable outcome of the Epstein release was malicious exploitation. As public interest surged, attackers rushed in.
LMG Security observed malware distributed earlier this year using Epstein-related filenames, and more recently, phishing sites posing as “Epstein archives.” These sites mimicked legitimate repositories and attempted to steal credentials or deliver malicious downloads.
“This is very, very common,” Durrin said. “Because there’s so much attention here, people are going to take advantage of that curiosity.”
This pattern shows up after every major news event: data breaches, celebrity scandals, court decisions, natural disasters. Attackers don’t need zero-days—they just need timing.
The FBI and CISA have repeatedly warned about news-driven phishing campaigns, including those tied to high-profile data leaks and geopolitical events. The Epstein files simply made the pattern visible to a broader audience.
The Streisand Effect: When Pulling Data Makes It Worse
The DOJ’s decision to pull and reissue some Epstein files amplified scrutiny rather than containing it. Attention narrowed onto the specific documents that changed—exactly the opposite of what was intended.
This phenomenon has a name: the Streisand Effect
In 2003, Barbra Streisand sued the California Coastal Records Project for $50 million after an aerial photo of her Malibu home appeared in a public archive. Before the lawsuit, the image had been viewed six times—two by her own attorney. After the lawsuit made headlines, over one million people viewed it. The case was dismissed, and Streisand was ordered to pay legal fees.
Trying to hide information often puts a spotlight on it. The Epstein files followed the same trajectory.
For organizations managing incidents, this matters. Communication and remediation decisions can unintentionally magnify risk.
Authenticating Data Under Pressure
The other half of the problem isn’t what you release—it’s what you trust.
Ransomware cases provide a clear example. Attackers often claim they’ve stolen sensitive data. Sometimes they have. Sometimes they haven’t.
“We’ve worked cases where criminals claimed to have data, but when we asked for proof, all they could provide were screenshots,” Durrin explained. In one case, attackers had been inside the environment but hadn’t actually exfiltrated anything. The victim still paid hundreds of thousands of dollars.
Authentication matters.
Effective verification doesn’t require deep cryptography expertise, but it does require discipline:
- Validate the source. Is the data coming from an authoritative, primary source?
- Check hosting and version history. Has the file been pulled, reissued, or altered?
- Use cryptographic checksums. Compare hashes of suspected leaked files against known-good internal copies.
- Look for digital signatures. They’re underused, but powerful indicators of authenticity and integrity.
- Sample before reacting. Confirm data is real, relevant, and actually yours.
These steps should be part of every incident response playbook.
What Organizations Should Do Now
You don’t need perfect systems. But you do need clear processes, defined accountability, and verification built into how decisions are made—before the next high-profile event forces a rushed response.
Organizations should focus on five practical actions:
- Assume AI will see what humans don’t. Treat all uploaded documents as fully readable.
- Use professional redaction tools—and verify the result.
- Document and enforce redaction and authentication processes. Make them repeatable, not ad hoc.
- Build verification into decision-making, especially during incidents.
- Train staff for news-driven phishing and malware.
If your organization handles sensitive documents, investigations, or public disclosures, this is the time to pressure-test your redaction practices, authentication workflows, and incident response assumptions.
LMG Security helps organizations do exactly that through penetration testing, advisory services, and training designed for today’s threat landscape.
Want a deeper breakdown? Catch the full CyberSide Chats episode for a practical discussion of redaction failures, AI risk, and how to build verification into your security program.
