In 2026, marking AI-generated content officially transitions from a voluntary industry initiative to a statutory obligation. How should enterprises respond?
If an AI-generated product image is modified and distributed across multiple platforms, how can we verify its original provenance?After an AI video undergoes editing, compression, or even screen capture (re-recording), causing the visible watermark to vanish, how do we trace it back to its source?When an AI-generated article is copied, rewritten, and forwarded, how can enterprises distinguish between the original AI output and subsequent human modifications?
As the cost of generating AI content continues to drop, a critical question emerges: How do we verify the origin, creator, and integrity of digital content?

AI Content Must Be "Certified" to Enter the Market

On September 1, 2025, China’s Measures for Labeling AI-Generated Synthetic Content (No. [2025] 2) and the mandatory national standard GB 45438—2025 came into effect simultaneously. Service providers are required to embed both explicit disclosures and implicit watermarks at the point of generation, while distribution platforms bear the responsibility for verification and user notification. One year later, this framework will be fully operational.

On August 2, 2026, Article 50 of the EU AI Act, regarding transparency obligations, will officially apply. AI-generated content must be marked in a machine-readable format. Violators face fines of up to €15 million or 3% of global annual turnover, whichever is higher.

Industry leaders have already taken action: Anthropic has embedded invisible statistical signatures (SynthID-Text) in Claude-generated text, while OpenAI, Adobe, Microsoft, TikTok, and others have adopted the C2PA (Coalition for Content Provenance and Authenticity) standard—with over 455 members—which has been formalized as an international standard under ISO 22144.

The signal is clear: Invisible watermarking + C2PA cryptographic signing is becoming the recognized technical pathway. Unlabeled AIGC content faces platform distribution restrictions, verification challenges, potential compliance penalties, and reputational risks. For enterprises with high-frequency content production and diverse distribution channels, this is a non-negotiable security baseline.

The challenge follows: How can we issue a truly "portable, verifiable, and tamper-evident" digital identity for every piece of AIGC content?

Issuing Tamper-Evident "Digital IDs" for AIGC Content

Adding an "AI Generated" badge to an image is straightforward. But when that image is screenshotted, cropped, compressed, or re-edited by another AI model, can its identity still be recognized? If a video undergoes editing, speed adjustments, filters, special effects, platform transcoding, secondary encoding, or even smartphone re-recording, does the watermark information survive? This requires a standardized capability framework.

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This year, Alibaba Cloud launched AI DeepSign, establishing an identity system for every piece of AIGC content that spans the entire lifecycle—from generation and circulation to verification and tracing. It covers all modalities, including text, images, video, and audio, meeting enterprise-grade AIGC security needs in high-value scenarios such as finance, media, and e-commerce.

Invisible Watermarking Capability: Addressing the challenge of recovering content after screenshots, edits, AI regeneration, or deliberate watermark removal, we provide three layers of protection:

AI-Editing Resistant Watermarks: Robust against semantic-level manipulations.
Segmented Material Watermarks: Extractable from just 1 second of video, resisting full-chain attacks including editing and platform compression.
Short-Drama Watermarks: Designed to withstand physical re-recording; effective on videos longer than 20 seconds with no perceptible loss in visual quality.

These capabilities extend to text, code, audio, databases, and models. Currently, the solution supports adding C2PA signatures and watermarks to 20 mainstream Large Language Models (LLMs).

Dual-Track Compliance: We orchestrate China’s National Standard implicit labeling and C2PA signing into a single workflow. The National Cryptography Track answers "Who is responsible for the content?" and "Was it AI-generated?", while the International Track answers "What is the provenance history of the content?" A single integration satisfies compliance requirements once and for all.

Verification and Tracing Closed Loop: Signing and watermarking occur instantly upon content generation, with "identity metadata" flowing synchronously with the file. During distribution, platforms and third parties can verify authenticity via standard APIs. In cases of theft or leakage, invisible watermarks and cryptographic credentials jointly pinpoint the content’s origin, providing solid evidence for legal recourse and forensics.

Scenario Validation: Anti-forgery signature verification for financial insurance policies, proof of originality for news media, counterfeit detection for e-commerce product images, and copyright/leak tracing for short dramas have all been successfully validated in real-world business environments.

Technical Leadership: Traceability Remains Even After Multiple Attacks

The true watershed moment for watermarking capability lies in its effectiveness under adversarial conditions.

Resistance to AI Editing: Holding the Line When Traditional Watermarks Fail

With advanced generative tools, attackers no longer need pixel-by-pixel manipulation; they can directly delete objects, replace backgrounds, alter character attributes, or regenerate scenes entirely. Against these "semantic-level attacks," Alibaba Cloud AI DeepSign covers 8 major types of mainstream AI editing techniques, including object addition/removal, attribute/behavior modification, background replacement, style transfer, and composite editing.

Full-Chain Attack Testing: 100% Watermark Extraction Success Rate

After applying editing, special effects, speed adjustments, and filters to 16 test clips, uploading them to platforms, and subjecting them to extreme compression (reducing file size from 19MB to 2.2MB), Alibaba Cloud AI DeepSign achieved a 100% watermark extraction success rate (internal test data).

Solving an Industry Challenge: Text Watermarking

Compared to images and video, text watermarking has long been considered a recognized industry hurdle:

Generation-time watermarking often requires intervening in model sampling and accessing internal probability distributions, making it incompatible with third-party API models;
Post-processing watermarking introduces additional latency and may degrade semantic integrity;
Relying solely on metadata results in easy loss during copy-paste operations.

Alibaba Cloud AI DeepSign breaks this deadlock with a "Signature + Watermark" dual-track approach: Through an innovative streaming chain-signing architecture, we extend the C2PA standard from "static content provenance" to "dynamic generated content provenance." Hashes are accumulated frame-by-frame during streaming output; any tampering with the content, order, or termination frames of any chunk leads to signature verification failure. Invisible text watermarks subtly adjust lexical embeddings, traveling with the text itself. They remain detectable even after copying and forwarding. Even when facing third-party black-box models where internal parameters are inaccessible, we achieve: Labelable, Verifiable, and Traceable.

Official C2PA Enorsement: Building Trust Anchors

Content identity must not only be recognizable but also cryptographically secure against credential forgery. AI DeepSign integrates with the official C2PA certificate signing system, compatible with C2PA v2.4 specifications. Key protection aligns with the L1 Assurance Level defined by C2PA, and signing certificates strictly adhere to normative certificate profiles. Signing private keys are fully managed within Hardware Security Modules (HSMs) certified for both Chinese National Cryptography Standards (GM/T) and FIPS, ensuring zero exposure of private keys to the business layer. Additionally, each manifest includes an RFC 3161 Trusted Timestamp, supporting Long-Term Validity (LTV)—verification conclusions remain valid even after certificate expiration.

As the marginal cost of AI-generated content approaches zero, "trust" becomes increasingly expensive. Alibaba Cloud AI DeepSign establishes a content identity infrastructure for the AIGC era: Watermarking and signing at the moment of creation, continuous verifiability throughout circulation, immediate detection of tampering, and precise tracing of leaks.

Let every piece of AI content possess its own true, tamper-evident "Digital Identity."

AI DeepSign quick start：
https://www.alibabacloud.com/help/en/ai-deepsign/getting-started/quick-start

Community

Alibaba Cloud AI DeepSign: Issuing a "Tamper-Proof Digital ID" for AIGC Content

AI Content Must Be "Certified" to Enter the Market

Issuing Tamper-Evident "Digital IDs" for AIGC Content

Technical Leadership: Traceability Remains Even After Multiple Attacks

Resistance to AI Editing: Holding the Line When Traditional Watermarks Fail

Full-Chain Attack Testing: 100% Watermark Extraction Success Rate

Solving an Industry Challenge: Text Watermarking

Official C2PA Enorsement: Building Trust Anchors

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