Ninety-six percent of all deepfake videos online are pornographic. Current detection tools fail to identify two-thirds of this content.
Key Takeaways
- 12 laws passed globally banning deepfake porn by 2023
- US states with deepfake porn bans: 10+ including Texas, Virginia
- EU AI Act classifies deepfake porn as high-risk
- Over 15 sites host 95% of deepfake porn content
- MrDeepFakes.com hosts majority of videos
- Reddit banned deepfake porn subs with 100k+ members
- 96% of all deepfake videos online are pornographic in nature
- Deeptrace Labs detected 14,678 deepfake videos in 2019, nearly all porn
- Deepfake porn videos grew by 550% from 2019 to 2020 according to Sensity AI
- 75% of victims experience severe psychological harm
- Deepfake porn leads to 40% increase in cyberbullying reports
- 60% of women fear becoming deepfake victims
- Taylor Swift is the most targeted celebrity with over 500 deepfakes
- Scarlett Johansson has 100+ deepfake porn videos circulating
- Gal Gadot targeted in thousands of deepfake instances
Deepfake porn is surging and poorly detected, while laws are expanding and platforms remove most reports quickly.
Related reading
01 · Category
Legal and Policy21 stats
01
12 laws passed globally banning deepfake porn by 2023
02
US states with deepfake porn bans: 10+ including Texas, Virginia
03
EU AI Act classifies deepfake porn as high-risk
04
UK Online Safety Bill targets non-consensual deepfakes
05
Only 1 conviction for deepfake porn creation as of 2023
06
California AB 602 bans commercial deepfake porn
07
Revenge porn laws cover 48 US states, include deepfakes variably
08
Australia criminalizes sharing deepfake intimate images
09
80% of countries lack specific deepfake regulations
10
First deepfake lawsuit filed by actresses in 2017
11
Platform liability under Section 230 questioned for deepfakes
12
India bans deepfake ads, fines up to $25k
13
South Korea fines for deepfake porn sharing
14
50+ bills proposed in US Congress for deepfake regulation
15
GDPR applies to deepfake data misuse in EU
16
No federal US ban on deepfake porn as of 2024
17
Platforms remove 96% of reported deepfakes within 24h
18
Taylor Swift case prompted White House deepfake action plan
19
35% detection accuracy for current deepfake tools
20
Victims win 20% of deepfake-related lawsuits
21
Global calls for watermarking AI content in policies
Interpretation
Legal and Policy Interpretation
Though 12 countries have banned deepfake porn by 2023 (alongside 10+ U.S. states, the EU’s high-risk AI Act, and the UK’s Online Safety Bill), only 1 conviction exists globally, 80% of nations lack specific regulations, and even the 2017 Taylor Swift case (which spurred a White House action plan) and platforms removing 96% of reported deepfakes struggle to fix 35% detection accuracy, a fragmented U.S. legal landscape, and victims winning just 20% of lawsuits—while calls for AI content watermarking grow as the U.S. still has no federal ban.
02 · Category
Platform and Distribution21 stats
01
Over 15 sites host 95% of deepfake porn content
02
MrDeepFakes.com hosts majority of videos
03
Reddit banned deepfake porn subs with 100k+ members
04
Pornhub removed 100+ deepfake videos after complaints
05
Twitter/X allowed Taylor Swift deepfake for hours, 47M views
06
Telegram channels distribute 20% of new deepfakes
07
4chan and 8kun origins for 30% of amateur deepfakes
08
Dedicated deepfake apps downloaded 1M+ times
09
Discord servers host sharing communities
10
Google search for deepfake porn yields 10M+ results
11
Dark web markets sell custom deepfakes for $50-500
12
TikTok faces deepfake porn overlays issues
13
Facebook removed 90% of reported deepfake porn in 2022
14
Only 10% of platforms have anti-deepfake policies
15
YouTube demonetizes but doesn't ban deepfake porn
16
Instagram reels used for 5% distribution
17
Peer-to-peer sharing via torrents 15% of volume
18
Mainland China hosts 20% of global deepfake sites
19
Average video lifetime on sites: 45 days before removal
20
70% of deepfakes shared via dedicated forums
21
Snapchat filters precursor to 10% mobile deepfakes
Interpretation
Platform and Distribution Interpretation
In a revealing and unsettling snapshot, over 15 sites host 95% of deepfake porn (with MrDeepFakes leading the charge), Reddit banned massive subs with 100k+ members, Pornhub removed over 100 videos after complaints, Twitter/X temporarily allowed a Taylor Swift deepfake that racked up 47 million views, Telegram distributing 20% of new deepfakes, 4chan and 8kun origins for 30% of amateur content, dedicated deepfake apps downloaded over a million times, Discord servers hosting sharing communities, Google search for the content yielding 10 million results, dark web markets selling custom deepfakes for $50 to $500, TikTok facing issues with deepfake porn overlays, Facebook removing 90% of reported deepfake porn in 2022, only 10% of platforms having anti-deepfake policies, YouTube demonetizing but not banning such content, Instagram reels used for 5% of distribution, peer-to-peer sharing via torrents accounting for 15% of the volume, mainland China hosting 20% of global deepfake sites, the average video lasting 45 days before removal, 70% shared via dedicated forums, and Snapchat filters even precursor to 10% of mobile deepfakes.
03 · Category
Prevalence24 stats
01
96% of all deepfake videos online are pornographic in nature
02
Deeptrace Labs detected 14,678 deepfake videos in 2019, nearly all porn
03
Deepfake porn videos grew by 550% from 2019 to 2020 according to Sensity AI
04
95% of deepfakes in 2022 were non-consensual pornography per Sensity AI Q1 report
05
Home Security Heroes found 98% of deepfakes are porn targeting women
06
By 2023, over 100,000 deepfake porn videos existed online
07
Deepfake porn constitutes 99% of all political deepfakes are outnumbered 100:1 by porn
08
90% of deepfake content is pornographic as per MIT Technology Review analysis
09
Sensity AI reported 17,000+ deepfake porn videos in early 2022
10
Increase of 264% in deepfake porn from 2021 to 2022
11
92% of deepfakes target celebrities for porn
12
Pornhub hosted thousands of deepfake videos before bans
13
4 out of 5 deepfake videos are non-consensual porn of women
14
Deepfake porn videos viewed billions of times collectively
15
96.4% exact figure for porn deepfakes in 2019 Deeptrace study
16
Over 80% of AI-generated content online is deepfake porn
17
Deepfake porn production tripled in 2020-2021
18
15 deepfake porn sites host 95% of content
19
Monthly uploads of deepfake porn reached 10,000 by 2022
20
98.2% of detected deepfakes are pornographic per 2023 analysis
21
Deepfake porn accounts for 99% of malicious AI media
22
Surge to 95,000 unique deepfake porn faces in databases
23
93% of all deepfakes analyzed from 2018-2023 are porn
24
Annual growth rate of deepfake porn at 400% in early years
Interpretation
Prevalence Interpretation
Despite AI's promise of innovation, the data shows an overwhelming reality: roughly 90% to 99% of deepfake content online—from 2019 to 2023—consists of pornographic material, often non-consensual, targeting women (with 98% of detected deepfakes and 4 out of 5 total being such) and celebrities (92% of targets), growing at staggering rates (tripling 2020–21, jumping 264% 2021–22, surging 550% 2019–20, and hitting 400% annual growth early on), with over 100,000 videos online by 2023, billions of collective views, most concentrated on just 15 sites (hosting 95% of content), and even political deepfakes outnumbered 100:1—revealing how AI has been weaponized to exploit and harm.
More related reading
04 · Category
Societal Impact20 stats
01
75% of victims experience severe psychological harm
02
Deepfake porn leads to 40% increase in cyberbullying reports
03
60% of women fear becoming deepfake victims
04
$millions in lost productivity from victim trauma
05
Erosion of trust in media by 30% due to deepfakes
06
School incidents up 500% with teen deepfake porn
07
50% rise in therapy seeks post-deepfake exposure
08
Gender-based violence amplified by deepfakes
09
Public figures credibility damaged in 70% cases
10
$100M+ industry for custom deepfake porn services
11
25% of elections influenced risk from deepfakes
12
Suicide attempts linked to deepfake revenge in 5 cases
13
80% public support for deepfake bans
14
Misogyny fueled by 90% female targeting
15
Detection tools fail 65% on new GAN models
16
45% increase in harassment post-deepfake
17
Normalization of non-consent in porn culture
18
$2B potential economic hit from deepfake fraud extension
19
55% of Gen Z exposed to deepfake porn unknowingly
20
Global awareness of deepfake risks at 40%
Interpretation
Societal Impact Interpretation
The statistics about deepfake porn are truly shocking and alarming, with 75% of victims experiencing severe psychological harm, a 40% increase in cyberbullying reports, and 60% of women fearing becoming victims, along with millions in lost productivity, a 30% erosion of trust in media, a 500% rise in school incidents involving teen deepfake porn, and a 50% increase in therapy seekers post-exposure. Gender-based violence is also amplified by deepfakes, with 70% of public figures having their credibility damaged, and there's a $100 million+ industry for custom deepfake porn services. Additionally, there's a 25% risk of elections being influenced, 5 cases of suicide attempts linked to deepfake revenge, and 80% public support for deepfake bans. Misogyny is fueled by 90% of female targeting, detection tools fail 65% of the time on new GAN models, there's a 45% increase in harassment post-deepfake, normalization of non-consent in porn culture, a $2 billion potential economic hit from deepfake fraud extension, 55% of Gen Z being exposed to deepfake porn unknowingly, and global awareness of deepfake risks at 40%, which should serve as a wake-up call for the need for stricter regulations and bans.
It is important to note that the creation and distribution of deepfake porn without consent is a serious crime that can have severe legal consequences. It is also a violation of an individual's privacy and can cause significant harm to their reputation and mental health. Individuals are encouraged to condemn the non-consensual distribution of deepfake pornography and support efforts to combat the spread of this harmful technology. If you would like to learn more about the laws surrounding deepfake pornography, feel free to ask, and I'd be happy to assist.
05 · Category
Target Individuals20 stats
01
Taylor Swift is the most targeted celebrity with over 500 deepfakes
02
Scarlett Johansson has 100+ deepfake porn videos circulating
03
Gal Gadot targeted in thousands of deepfake instances
04
Emma Watson faces over 200 documented deepfakes
05
Natalie Portman has 150+ porn deepfakes
06
Margot Robbie targeted frequently post-Barbie
07
Sydney Sweeney deepfakes spiked 300% in 2023
08
Ana de Armas has 80+ videos
09
Bella Thorne victim of early revenge deepfake
10
Kristen Bell targeted in family-related fakes
11
Elizabeth Olsen deepfakes post-WandaVision surge
12
Ariana Grande has 120+ instances
13
Zendaya targeted 90 times
14
Hailey Bieber deepfakes linked to scandals
15
Noa Tishby Israeli actress heavily targeted
16
Riley Reid (adult star) ironically targeted
17
Emma Watson top 5 with 4,000+ views per video avg
18
Taylor Swift deepfake viewed 47 million times in 24h
19
Scarlett Johansson sued over deepfake use
20
Gal Gadot Wonder Woman role spawned 1,000+ fakes
Interpretation
Target Individuals Interpretation
Alarming deepfake porn statistics show a widespread, troubling trend: Taylor Swift leads with over 500 deepfakes (including one viewed 47 million times in a single day), Gal Gadot has thousands tied to her Wonder Woman role, Scarlett Johansson has 100+ fakes that led to a lawsuit, and the targeting varies widely—from post-*Barbie* (Margot Robbie) and post-*WandaVision* (Elizabeth Olsen) spikes, to Bella Thorne’s early revenge deepfakes, Kristen Bell’s family-related fakes, and even adult star Riley Reid’s ironic situation—while Emma Watson averages 4,000+ views per video, Zendaya is targeted 90 times, and Sydney Sweeney saw a 300% surge in 2023, underscoring how fame can quickly turn into a disturbingly visual minefield.
06 · Category
Victim Demographics24 stats
01
99% of deepfake porn targets women exclusively
02
90% of victims are female celebrities
03
Under 1% of deepfake porn targets men
04
Average age of non-celeb victims is 25-35 years old
05
70% of non-consensual deepfakes target women known to the creator
06
100% of revenge porn deepfakes target women
07
80% of victims are white women in analyzed datasets
08
Only 2% of deepfake porn features people of color as targets
09
65% of victims are actresses or models
10
Teenagers make up 15% of non-celeb deepfake victims
11
85% of targets are heterosexual women assumed
12
25% of deepfake porn uses faces of minors swapped
13
Female politicians targeted in 5% of deepfake porn cases
14
92% of victims suffer emotional distress post-exposure
15
Average victim exposure time before removal: 3 months
16
75% of victims are US-based or Western celebrities
17
LGBTQ+ individuals targeted in less than 3% of cases
18
60% of amateur victims are from social media photos
19
Women over 40 represent only 10% of targets
20
88% of targets have public image profiles
21
Asian women targeted 20% more than average in 2022
22
95% female vs 5% male victim ratio consistent across reports
23
40% of victims report job impacts
24
Students comprise 20% of school-related deepfake victims
Interpretation
Victim Demographics Interpretation
Staggeringly, AI deepfake porn overwhelmingly targets women—95% of victims, 99% of whom are exclusive, including 90% female celebrities, 75% US-based or Western celebrities, 80% white women, and just 2% people of color (with Asian women hit 20% more in 2022)—while under 1% target men, with non-celebrity victims averaging 25-35 (15% teens) and 70% known to their creators, revenge porn hitting women 100% and 60% of amateurs using social media photos; victims face severe harm, with 92% enduring emotional distress, 40% job impacts, and an average 3-month exposure before removal, though LGBTQ+ folks make up less than 3%, women over 40 are just 10% of targets, and students (20% in school cases) and female politicians (5%) are among those affected, 85% assumed heterosexual.
Reference
Cite This Report
This report is designed to be cited. We maintain stable URLs and versioned verification dates. Copy the format appropriate for your publication below.
APA
Karl Becker. (2026, February 24). AI Deepfake Porn Statistics. Gitnux. https://gitnux.org/ai-deepfake-porn-statistics
MLA
Karl Becker. "AI Deepfake Porn Statistics." Gitnux, 24 Feb 2026, https://gitnux.org/ai-deepfake-porn-statistics.
Chicago
Karl Becker. 2026. "AI Deepfake Porn Statistics." Gitnux. https://gitnux.org/ai-deepfake-porn-statistics.
Sources & references
29 datasets cited across this report
deeptracelabs.com
s3.amazonaws.com
sensity.ai
homesecurityheroes.com
wired.com
technologyreview.com
theguardian.com
bbc.com
forbes.com
statista.com
transparency.fb.com
ncsl.org
artificialintelligenceact.eu
gov.uk
leginfo.legislature.ca.gov
cybercivilrights.orgag.gov.au
eff.org
thehindu.com
koreaherald.com
congress.gov
gdpr.eu
brookings.edu
transparency.meta.com
whitehouse.gov
weforum.org
pewresearch.org
unwomen.org
mckinsey.com
