惯性聚合 高效追踪和阅读你感兴趣的博客、新闻、科技资讯
阅读原文 在惯性聚合中打开

推荐订阅源

H
Help Net Security
腾讯CDC
Threat Intelligence Blog | Flashpoint
Threat Intelligence Blog | Flashpoint
WordPress大学
WordPress大学
Engineering at Meta
Engineering at Meta
M
MIT News - Artificial intelligence
H
Hackread – Cybersecurity News, Data Breaches, AI and More
让小产品的独立变现更简单 - ezindie.com
让小产品的独立变现更简单 - ezindie.com
宝玉的分享
宝玉的分享
阮一峰的网络日志
阮一峰的网络日志
N
Netflix TechBlog - Medium
罗磊的独立博客
G
Google Developers Blog
Microsoft Azure Blog
Microsoft Azure Blog
美团技术团队
MongoDB | Blog
MongoDB | Blog
雷峰网
雷峰网
Recent Announcements
Recent Announcements
The Cloudflare Blog
小众软件
小众软件
大猫的无限游戏
大猫的无限游戏
The GitHub Blog
The GitHub Blog
博客园 - Franky
博客园 - 三生石上(FineUI控件)
T
Tenable Blog
A
Arctic Wolf
www.infosecurity-magazine.com
www.infosecurity-magazine.com
cs.AI updates on arXiv.org
cs.AI updates on arXiv.org
cs.CL updates on arXiv.org
cs.CL updates on arXiv.org
V2EX - 技术
V2EX - 技术
OSCHINA 社区最新新闻
OSCHINA 社区最新新闻
T
Threat Research - Cisco Blogs
D
Docker
Y
Y Combinator Blog
博客园 - 叶小钗
PCI Perspectives
PCI Perspectives
P
Privacy & Cybersecurity Law Blog
Security Archives - TechRepublic
Security Archives - TechRepublic
C
CERT Recently Published Vulnerability Notes
P
Proofpoint News Feed
NISL@THU
NISL@THU
C
Cyber Attacks, Cyber Crime and Cyber Security
GbyAI
GbyAI
Application and Cybersecurity Blog
Application and Cybersecurity Blog
T
The Exploit Database - CXSecurity.com
P
Proofpoint News Feed
Spread Privacy
Spread Privacy
L
LangChain Blog
N
News and Events Feed by Topic
量子位

seangoedecke.com RSS feed

Impro is a handbook for running a cult Overtraining as the path to human-like AI What does "playing politics" mean for software engineers? In defense of not understanding your codebase Blog about things you don't understand yet Text AI watermarks will always be trivial to remove Saying the obvious thing AI inference is obviously profitable AI GPUs probably live longer than three years Doing nothing at work Working with product managers Anti-AI nostalgia and the cult of the past Weird projects I shipped with AI Build agents, not pipelines The famous o3 "GeoGuessr" prompt did not work Prompts are technical debt too The just-say-no engineer was a ZIRP phenomenon How I use LLMs as a staff engineer in 2026 DeepSeek-V4-Flash means LLM steering is interesting again AI datacenters in space do not have a cooling problem Thinking Machines and interaction models The left-wing case for AI AI makes weak engineers less harmful Notes on incidents Why hasn't longer-horizon training slowed AI progress? Why I don't like the "staff engineer archetypes" Software engineering may no longer be a lifetime career Blood in the datacenter Many anti-AI arguments are conservative arguments Programming (with AI agents) as theory building Working on products people hate Engineers do get promoted for writing simple code Big tech engineers need big egos I don't know if my job will still exist in ten years Giving LLMs a personality is just good engineering What's so hard about continuous learning? Insider amnesia LLM-generated skills work, if you generate them afterwards Two different tricks for fast LLM inference On screwing up Large tech companies don't need heroes Getting the main thing right How does AI impact skill formation? You have to know how to drive the car
C2PA only works if everything is signed
2026-07-06 · via seangoedecke.com RSS feed

The European Union AI Act is Europe’s attempt to comprehensively regulate AI usage. A big part of that is the requirement that AI-generated content be identifiable: either tagged with a watermark or with what the Act calls “digitally signed metadata”1. Since all this becomes enforceable in a month, it’s worth figuring out if it makes any sense. I recently discussed AI watermarking at length in Text AI watermarks will always be trivial to remove. What about digitally signed metadata?

The most well-known implementation of digitally signed metadata is C2PA Content Credentials, which incorrectly2 claims to be the technology that the AI Act gives as an example of how to do signed metadata properly. The idea here is that every single image file should contain unspoofable authorship metadata. Here’s my position on it:

  1. C2PA broadly makes sense and is a good idea
  2. It is pointless to use C2PA for AI-generated images only
  3. It will take many years for C2PA to be adopted across all images
  4. Because C2PA makes such great safety theater, we’re going to see a lot of hue and cry about it long before it becomes useful

Lots to unpack. Let’s start by considering images, since that’s the easiest case.

How C2PA signing works

When an AI tool generates an image, that tool should include a “made by ChatGPT” disclaimer in that image’s metadata. Likewise, when a camera takes a photo, that camera should include a “taken by a camera” disclaimer. C2PA uses two strategies to protect this metadata:

  1. The metadata must be signed by some trusted private key
  2. The metadata contains a hash of the file’s contents, so you can’t copy an existing signature onto a new file

Each physical camera (or phone) has its own private key, for obvious reasons3. How do we know that those millions of private keys are trusted? Via PKI, like HTTPS: each camera’s private “certificate” (which contains its public key) is signed by the manufacturer’s well-known private key, so the chain of authenticity can be verified as long as you have (say) Apple’s root public key4.

What happens if you then edit your photo in Photoshop? Photoshop will leave the camera’s metadata untouched, but will layer a “also, Photoshop was used” piece of metadata over the top, signed with Adobe’s private key (well, with the private key associated with your official copy of Photoshop, which is signed by Adobe’s official private key).

Likewise, if you ask ChatGPT to generate an image for you, ChatGPT will sign its “made by ChatGPT” metadata with OpenAI’s private key. In theory, every single image could contain unforgeable C2PA metadata, allowing software like Twitter to trivially distinguish real photos from fake ones.

C2PA needs more regulation to boost adoption

Right now, C2PA does not have anything like the adoption it’d need to work. It’s hard to find hard data on how many images in the wild use C2PA, but FotoForensics reports around a dozen per week (so around 600 out of the 900,000 images processed each year). This is even worse than it sounds, because basically all of the signed images are AI-generated. The adoption rate of C2PA for human-generated images is much, much lower: so far, Google’s Pixel 10 is the only phone camera to sign photos by default. The iPhone doesn’t sign photos.

If almost all AI images are C2PA-signed, but almost no human-generated images are, consumers have no reliable way of identifying AI content, because anyone who wants to pretend their AI content is human can simply remove the signature. For C2PA to succeed, it needs to be on every camera and every phone, so that a photo with no signature is rare and suspicious.

Is that realistic? Actually, I think it is. The appetite (at least in the EU) to regulate AI will increase over time, and while the current EU AI Act only mandates that AI-images are tagged (which by itself is useless), it’s plausible that some future regulation will enforce tagging of all images.

Another adoption problem that must be solved for C2PA to work is preservation. Right now, if you download a C2PA-tagged image, send it as a Facebook message, then re-download it, the C2PA manifest is stripped out. Most images we see on the internet have passed through some social media asset server at least once. All of these social media companies would need to update how they re-encode image content in order to preserve the C2PA data5. This would almost certainly require more regulation: C2PA adds tens or hundreds of kilobytes to each file, which at social media scale is big money6.

Forging C2PA signatures

Could a clever attacker forge a C2PA signature? Kind of. Neal Krawetz, who seems to have led the anti-C2PA charge, points out that with a camera development kit it’s straightforward to trick a digital camera into thinking that it’s taking an image when in fact it’s being fed one. This is very much not my area, so please write in if you know more about camera hardware and you think I got this wrong. I suppose you could also take a photo of an AI image on a screen, though I imagine you’d have to be careful to make it look real.

If you exclude physical attacks on a digital camera, I think C2PA is more robust. You can sign a photo with a self-signed certificate, but the C2PA spec and docs say that validators must check that your certificate bubbles up to the official C2PA trust list. This list currently contains only 26 certificates, and there’s a whole process for being added to it. That’ll slow down adoption, but at least it makes it hard to forge7.

Other file types and concerns

We’ve been talking exclusively about images, but it’s more or less the same story for any type of content. If the file doesn’t support JUMBF metadata (say, an Excel file or a PDF), then the C2PA metadata has to live in a “sidecar”: a separate .c2pa file, probably on some Microsoft or Adobe content server, which contains the signed checksum and the data about who created the file.

However, the distinction between “real” and AI-generated content is fuzzier when you’re not talking about images. Here’s a trivial example: if I ask ChatGPT to create an Excel spreadsheet for me, the file will be tagged as AI-generated, but I can simply copy/paste the content into a new Excel doc and save it, which will tag it as human-generated8. There’s no software tool that can identify when I’m retyping some AI-generated text (except for perhaps text fingerprinting, which has its own raft of issues).

There are also interesting questions around key management. ChatGPT and other AI tools have an easy problem — their users are all online, and so the files can be signed server-side — but how do you sign files created via Photoshop/Excel/Word? If the user doesn’t have internet, do you use some kind of local key? If so, how do you prevent that key being extracted and used to sign AI-generated content?

Finally, is it a civil liberties problem to automatically fingerprint every photo? Does it make it impossible to be a whistleblower if every photograph can be traced back to your camera? I think this is a complicated question, but in short: I’d expect whistleblowers to already strip EXIF metadata from their images, C2PA metadata is similarly trivial to strip out, and overall I think image attribution is positive for whistleblowers because it heads off “this was AI-generated” responses.

Conclusion

C2PA is probably here to stay. But it isn’t useful now, and won’t be useful until two huge programs of technical work are completed:

  • Every camera manufacturer (including phones) must C2PA-sign all images by default
  • Every social media company must retain the C2PA metadata on uploaded images

This will be a long organizational process, since each manufacturer must go through the approvals process (or decide to start their own competing system), evaluate the legal ramifications of storing attribution data in images, and so on. It will be a long technical process, because C2PA metadata is a substantial fraction of image sizes: storing it will add many petabytes of content.

Of course, just because C2PA isn’t useful doesn’t mean we’re not all going to do it. Lots of companies are under pressure to signal that they care about AI safety and to head off regulatory attack. “We’re cryptographically signing AI-generated content” is a compelling “we’re doing something” pitch, particularly for people who aren’t technically savvy enough to understand the limitations. In the near term, I expect large AI-involved companies to invest a substantial amount of engineering effort in C2PA-related activity.

In the long run, once everyone gets on board, I think C2PA could end up working well. It’s awkward in some ways, but “attest content via a PKI certificate chain” is a good idea.

Is it possible to defeat? Yes, of course. By design, private keys will be in the user’s hands — in their cameras, in their local versions of Photoshop or Microsoft Word, in their phones — so sufficiently technical users will be able to crack them out or use them to sign whatever content they want. I still think C2PA will end up stemming the tide of AI content, because most users are not going to be sophisticated enough to perform attacks like this. However, we should still retain some skepticism of unlikely-looking content, even if it has “created by a human” in its C2PA metadata.


If you liked this post, consider subscribing to email updates about my new posts, or sharing it on Hacker News.

Here's a preview of a related post that shares tags with this one.

Text AI watermarks will always be trivial to remove

The European Union AI Act will begin to be enforceable in August 2026, one month from now. One of the biggest new requirements is Article 50, which requires all AI outputs to be “detectable as artificially generated”. In other words, if LLM providers want to do business in the EU, they will have to apply a watermark to their outputs: some hidden signature that can be used to identify AI content.
Continue reading...