Deepfake Safety: Five Things You Can Do Today

The generation of images, videos, and voices through artificial intelligence is evolving at a pace that demands we establish clear criteria and good habits to defend ourselves from the dangers of abusing these technologies. Deepfakes are already part of our everyday online life, so it is a very good idea to start adopting today and gradually internalizing small resources that help us identify signs of manipulation and protect our digital identity. Let’s talk about detection and our personal safety when defending ourselves against deepfakes.

What Are Deepfakes

Deepfakes are synthetic content —whether video, image, or audio— created or modified with artificial intelligence models capable of imitating faces, voices, and gestures with simply astonishing realism. The technique relies on generative networks that learn a person’s distinctive patterns and reproduce them in new scenes with high precision.

That realism is precisely the core of the challenge deepfakes represent, because while a few years ago we could notice them quickly, now with each iteration of the tools their plausibility increases and visible artifacts decrease, making them much harder to detect. With this perspective in mind, the most useful approach is probabilistic: detection gives us signals and degrees of confidence, and by combining multiple pieces of evidence and checks we exponentially increase our chances of success.

For more depth in fundamentals and examples, this guide on deepfake meaning and deepfake detection systems provide the basics for understanding the risks and the vocabulary we use to analyze and make sense of this phenomenon. With this foundation, let’s talk about learning to detect deepfakes with simple habits and everyday tools.

Five Practical Ways to Detect Deepfakes Today

The complexity of the task forces us to establish a method based on observation, contrast, and verification so that our safety against deepfakes becomes a natural part of our daily browsing on social media, messaging, and video platforms. Let’s go over five practices that combined give us the highest accuracy, both on screen and when listening to audio.

Scrutinize Facial Features and Movements

We begin with the face, because small inconsistencies in expressions, blinking, gaze, or skin texture are the first clues to uncover even the highest-quality synthetic generation.

With practice, we will be able to detect subtle deviations. Where to start? With this checklist of visual signs:

• Irregular blinking or blinking spaced too far apart compared to the natural patterns of the person in other authentic videos and within the same context.
• Skin with uniform plasticity, blurred pores, or a strange shine in areas that in real life show microtextures and more organic variation, even when makeup has been applied.
• Teeth, tongue, or mouth corners with soft edges, dentition that seems to change between shots, or implausible alignments in very close close-ups.
• Jawline and hairline edges with slight feathering, imperfect blending with the background or with accessories such as scarves and hats. Keep in mind, however, that background blur effects in some video call apps can produce very similar errors.
• Misalignment between facial microgestures and the message content, with delayed smiles or eyebrows moving half a second late.
• Earrings, beards, or glasses that vibrate, change shape, or intermittently lose sharpness as the head moves.
• Eyes with reflections that change without a real change in the environment, incongruent mirrored highlights, or duplicated catchlights.

If possible, carefully observing the person’s face with the video paused and reviewing some parts frame by frame helps us detect deepfakes with sound judgment and increase our confidence in doing so.

Check for Incongruities in Lighting and Shadows

Light tells the truth of the space, and precisely for that reason lighting and shadow inconsistencies give us key clues about generated or altered compositions. The physics of the environment is our best reference when paying close attention.

What to look at with special care:

• Facial shadows changing direction compared to the predominant shadows in the background or overall scene, with lines crossing where a real source should unify the fall.
• Reflections in glasses, eyes, or metallic surfaces that ignore environmental lights, with floating highlights unrelated to the movement of the light source, if it should move.
• Hair lighting notably different from facial tone, with strands too flat or locks not absorbing light as expected.
• Skin and clothing highlights inconsistent between frames, with unexpected flashes on cheeks or forehead while the rest of the shot remains stable.
• Shadows that are too harsh in some areas and diffuse in others despite being at the same distance and made of equivalent materials in the same scene.

When the video allows pausing, observing glasses, jewelry, and the shadow lines around the nose and neck helps us identify deepfakes with great reliability.

Analyze Audio and Speech Patterns

The audio track also offers many signals: rhythm, timbre, breathing, sibilance, and explosive consonants are the fingerprints of a voice where voice clones have more difficulty. Comparing with an authentic clip increases the detection margin, although this is not always possible.

What to focus on in the audio track? These five points:

• Speech rhythms that are too uniform, with identical pauses and repeated intonations in different parts of the conversation, even when covering different or more spontaneous topics.
• Breathing appearing in strange spots, compressed air fade-ins, or completely clean silences between words that sound unnatural.
• Slight mismatch between lips and phonemes, with plosives (p, b) and fricatives (f, s) not syncing precisely.
• Timbre preserved without variation when changing volume, without the typical roughness of the human voice when forcing it louder or softer.
• Abrupt transitions between phrases, with cuts or gating jumping between parts of communication.

A simple A/B comparison with interviews or original recordings should be enough. If not, we must sharpen our ear, especially if we lack visual support to gather more data.

Practice with Real vs. Fake Content

Training the eye and ear makes the difference, because our basic intuition develops by exposing ourselves first to real clips and then to synthetic ones. Watching AI-generated content is always a good idea, as we learn its signature marks.

To gain fluency:

• Participate in quizzes and experiments from universities and media that present real/fake pairs and conclude with explanations after each attempt.
• Create playlists with confirmed examples, saving notes on the traits we detect to repeat the pattern in other cases.
• Practice with video screenshots and audio waveforms, pausing and analyzing areas where artifacts or inconsistencies appear.
• Discuss our findings with friends and family in small weekly challenges, building a certain culture of deepfake protection in our own environment.

With short sessions, practical training is the best and most important help for detecting deepfakes quickly.

Closeup of woman using laptop with white screen in dark home setting, copy space

Stay Updated on Detection Techniques

Technology changes fast, so keeping up with deepfake detection tips expands our tools while reinforcing good habits of attention when reviewing sensitive content. A couple of good sources make all the difference. Some suggestions:

• Follow newsletters and alerts on dark AI with case studies, new benchmarks, and verification playbooks applicable to social media.
• Keep an updated cheatsheet —our own or from a reliable source— with a short list of warning signs and links to trusted public verifiers.

With even a light flow of technical news, this periodic upskilling helps us keep our criteria current and react better to new manipulation techniques.

Additional Tips for Personal Digital Safety

Beyond detection, we should care for our digital hygiene, because the combination of critical thinking and the right tools are the two keys to reducing risks and protecting our identity. Let’s look at some guidelines.

First, mindset: a skeptical approach helps us evaluate each piece of content as a hypothesis awaiting verification before drawing conclusions. This mindset prevents shortcuts, avoids overreacting to content, and favors calm decisions when a video or audio tries to provoke the opposite.

Second, processes: checking source, date, context, and cross-posting helps us detect suspicious duplications and understand whether the material fits with confirmed facts. Searching for the original version, identifying who recorded it, and reviewing comments from media and experts will always give us greater clarity.

Third, support tools: scam detectors such as the Avast Scam Detector Tool with link, domain, and scam pattern analysis help us filter the traps that accompany many deepfakes. If a video leads to a website trying to gather personal data or push urgent payments, that prior inspection blocks it before exposure even becomes a threat.

Fourth, device defense: our antivirus is tasked with blocking malware, phishing, and spyware, which quickly reduces the attack surface linked to deepfake campaigns. Having a trusted antivirus such as Avast Free Antivirus is key to avoiding malicious downloads and hidden payloads that often accompany manipulated pieces.

Fifth, identity and privacy: properly managing our profiles, passwords, and two-factor authentications helps prevent others from capturing material for impersonation or voice cloning.Minimizing our public biometric traces —for example, those left by high-quality audio— reduces material available for possible imitations.

Stay Vigilant, Stay Safe

Digital security relies above all on the habits we repeat daily. That’s why it is worth turning the five practices on this list into a routine we can apply every time a piece of content makes us doubt. Eyes and gestures, light and shadows, voice and rhythm, comparative practice, and constant updating help us detect deepfakes with ease.

Good practices with our devices, a protected ecosystem with antivirus and analysis tools help us reduce risks and consistently shield our online identity.

Spreading these guidelines within our close circle helps friends, family, and colleagues adopt deepfake protection as part of their good habits and raises the quality bar of circulating content.

Taking a few seconds to cross-check facial traits, lighting consistency, and voice synchrony helps us make better decisions before amplifying a piece of content. With that small margin of attention, combined with the right tools and regular updating, our online day-to-day quickly becomes much safer.