Malicious actors regularly bypass generative-AI safeguards to flood social media platforms with realistic fakes content. Time to stop spreading their lies!

As reported in the NY Times recently, generative AI tools such as Sora have been abused by malicious actors as well as hacktivists to spread lies and half-truths with realistic-looking videos.

With careful context-aware placement, fake videos can be easily created and then disseminated online, supposedly portraying “real events” such as protests, fraud, and celebrity scandals, flooding social media and eroding trust in visual proof.

Some of the content is explicitly labeled as “AI generated”, while others are not. How can anyone trust what they see in social media posts when we cannot even rely on watermarks and telltale signs of fake content? Malicious actors have even been able to bypass Sora’s recently-implemented measures to stop users from abusing its powerful features.

Stay vigilant with these tips

Here are some advanced detection methods, scam defenses, organizational strategies, and mindset shifts to bear in mind and also spread to friends and contacts. These practical steps will hopefully empower individuals, businesses, and communities to verify content, harden defenses, and spread awareness effectively.​

Core visual signs of AI fakery in faces and bodies

Start with faces: AI fakes show unnatural symmetry, plastic-like skin without pores or blemishes, and stiff micro-expressions.

Real humans twitch asymmetrically, while synthetics freeze or over-synchronize.

Eyes betray fakes through rare blinking, drifting gazes, or reflections mismatched to the scene; zoom in on teeth and mouth interiors for grotesque artifacts like melting edges.

Hands and bodies reveal flaws: extra/missing fingers, morphing shapes during gestures, or unnatural poses where arms bend impossibly. Sora clips often glitch on complex interactions, like food not deforming realistically in mouths.

Physics, lighting, and environment cues

Scrutinize physics:

Objects phase through each other, defy gravity with floaty trajectories, or glide without friction — watch hands pass through bags or crowds with looping identical pedestrians.

Lighting inconsistencies abound: shadows misalign, highlights flicker unnaturally, or reflections in glasses/eyes depict absent scenes.

Backgrounds subtly warp frame-to-frame, a diffusion model hallmark; pause and step through frames to spot “soft video” blurring on edges. In propaganda featuring crowds, Sora may fail here, with group shadows in the video clashing, or elements blending into the AI-generated bodies of “people”.

Audio sync and voice anomalies

Lip-sync desynchronizes by milliseconds. Also:

Cheeks puff oddly or jaws lag speech, amplified in slow-motion.

Voices lack natural reverb, breath pauses, or prosodic inflections, sounding robotic and overly clean without throat infrasound below 20Hz.

For serious deepfake analysis, use free tools such as Audacity for spectrograms: Synthetic videos show uniform formants and missing emotional variance.

Test stress responses — real audio pulses with heartbeats; fakes stay flat.

Biometric and behavioral red flags

Advanced checks reveal absent blood flow (no subtle skin color pulses) or heartbeat mismatches via chest micro-movements. Also:

Gaits jerk unnaturally — knees lock, feet float — or grips phase through objects.

In group scenes, identical behavior patterns across “individuals” signal loops. Sora excels at singles but stumbles on dynamics like wind affecting hair inconsistently or sweat absent during exertion.

Essential detection tools

Upload to free scanners:

Deepware, Hive Moderation, Sensity AI, Truthscan, or Reality Defender flag Sora-specific patterns despite watermark removal.

SOCRadar and Deep Media offer multimodal fusion (video/audio/text) with 95% accuracy via global heatmaps.

Browser extensions such as InVID-Verification enable reverse searches, provenance tracing, and C2PA metadata checks from Adobe/Microsoft.

No tool is foolproof — combine with manual reviews as AI evolves.

Scam and propaganda defenses

For family emergency scams, use pre-shared “safe words” AI cannot guess; hang up on unsolicited video calls and callback via verified numbers. For businesses: restrict approvals to hardware tokens or in-person; deploy Pindrop-like guards for lip-sync audits. Spot propaganda by agenda-pushing: Isolated viral content lacks eyewitnesses or multi-angles scream fake. Reverse-image search frames; trace content posters: new accounts with bot-like amplification indicate malicious ops.

Platform habits and policy advocacy

Enable AI labels on X/Meta/TikTok; report unmarked content. Petition for EU AI Act-style mandates on provenance. Analyze networks for bot swarms — ask “Cui bono?” (who benefits?). Diversify beyond algorithms to trusted outlets.

Training and long-term mindset

Practice daily: All video content is suspect until proven real. Analyze suspicious viral content frame-by-frame, slow audio 0.5x, and log patterns. Also:

Quarterly forensics updates keep pace: detection trails generation by months.

Cultivate pause habits: Force 10-second breathers before sharing any content to other groups.

Question the sensationalism of a post as an overarching sign of bad intent. Build communities for peer verification; share this guide to amplify resilience.

Build a default sense of skepticism without letting paranoia take over logic: truth withstands scrutiny; fake contents crumble upon deep verification and cross referencing with reliable information sources.

Sora’s ability to create realistic content demands vigilance, but layered checks — visual, audio, tools, context — can help social media users detect enough suspicious signs to stop making the content go viral.

Remember to empower others: Spread the cautionary warnings, host awareness sessions, demand transparency from social media platforms — to stay safe in the disinformation age.