Content Generation & Moderation

Generate with boundaries.
Moderate before publish.

Control creative AI and multimodal moderation pipelines with provenance, policy checks, and human review for high-risk outputs.

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solution workbench
incidents
3
products
2
evidence
full trace
failure modes
Deepfake campaigns and harassment
A viral deepfake depicted Martin Luther King Jr. endorsing a candidate, one in six congresswomen report non-consensual AI porn, and scammers cloned CEO voices to steal $243k—all eroding trust in synthetic media.
test
Copyright ghosts in AI output
Getty sued Stability AI after its watermark reappeared in generations, and newspapers ran AI-generated reading lists full of made-up books and author bios, forcing retractions.
test
Unmoderated glitches went viral
Snapchat's My AI posted a random Story before freezing, and Brave researchers showed that hidden text in images could hijack Perplexity's Comet browser—demonstrating how fast visual exploits or bugs become memes.
test
controls
Asset Management
Runtime Security
Provenance and moderation logs

Prompt and output policy

Control creative AI and multimodal moderation pipelines with provenance, policy checks, and human review for high-risk outputs.

Test the realistic attack paths

3 field failure modes become adversarial campaigns tailored to this deployment.

Convert findings into controls

Asset Management, Runtime Security keep the workflow bounded after launch.

Built for this workflow

Controls that match
the deployment.

  • Brand teams spinning up spokespeople, AR loops, or hero imagery from curated prompt packs and asset libraries.
  • Streaming platforms muting policy violations, blurring disallowed scenes, and queuing human review before a clip goes live.
  • Marketplaces and UGC communities triaging millions of uploads for CSAM, gore, or extremist propaganda before publishing.
content-generation-and-moderation.yaml
# Apply the solution playbook.
# $ ga solutions apply content-generation-and-moderation

deployment: content-generation-and-moderation
assets:
  - prompt packs
  - media assets
  - review queues
test_against:
  - Deepfake campaigns and harassment
  - Copyright ghosts in AI output
  - Unmoderated glitches went viral
runtime_controls:
  - AI Security Asset Management
  - AI Runtime Security
evidence: traces,citations,owners

Field evidence

Failure modes worth testing.

Content Generation & Moderation deployments fail when the model gets more trust than the workflow can safely absorb. These examples become concrete tests, not generic awareness copy.

incident

Deepfake campaigns and harassment

A viral deepfake depicted Martin Luther King Jr. endorsing a candidate, one in six congresswomen report non-consensual AI porn, and scammers cloned CEO voices to steal $243k—all eroding trust in synthetic media.

The HillThe MarkupForbes
incident

Copyright ghosts in AI output

Getty sued Stability AI after its watermark reappeared in generations, and newspapers ran AI-generated reading lists full of made-up books and author bios, forcing retractions.

Ars TechnicaPhiladelphia Inquirer
incident

Unmoderated glitches went viral

Snapchat's My AI posted a random Story before freezing, and Brave researchers showed that hidden text in images could hijack Perplexity's Comet browser—demonstrating how fast visual exploits or bugs become memes.

TechCrunchBrave

How General Analysis helps

Product controls for this use case.

The playbook connects discovery, automated red teaming, and runtime protection so controls stay specific to the deployment instead of becoming a generic policy layer.

General Analysis

AI Security Asset Management

Scan training sets, prompt templates, and RAG indexes for poisoned instructions, PII, or unlicensed work so generators never learn from material they cannot legally output.

General Analysis

AI Runtime Security

Enforce style guardrails, watermark/NSFW/extremist detectors, and human review gates for sensitive prompts or live streams while logging provenance metadata.

How the playbook runs

Map

Identify the assets and owners

Inventory prompt packs, media assets, review queues and the identities, tools, and data paths attached to the workflow.

Attack

Replay the relevant incidents

Turn field failures into adversarial prompts, multi-turn tests, tool-use probes, and policy traps for this deployment.

Enforce

Ship controls into production

Apply prompt and output policy, review-gated publishing, and escalation rules where the workflow needs them.

Prove

Keep evidence attached

Provenance and moderation logs

FAQ

Questions teams ask before launch.

Practical answers for deploying content generation & moderation with controls that security, legal, and operators can inspect.

Runtime guardrails enforce your brand guidelines at two stages: at prompt time, where brand palettes, composition constraints, and banned themes are injected into the generation context, and at output time, where post-render filters scan the result for policy violations, off-brand elements, or harmful content. For high-impact creatives—campaign hero images, video thumbnails, or public-facing ad copy—you can require dual human approvals before the asset is cleared for publishing. The system logs every generation attempt, applied constraint, and approval decision for your creative ops team to review.