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Why do people (and robots) call but stay silent? | Kaspersky official blog

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Analysisai
Published: 07/30/2026 (07/30/2026, 11:02:08 UTC)
Source: Kaspersky Security Blog

Description

Your phone rings, you pick up and say hello. On the other end: total silence. No one answers, and the call abruptly disconnects. If you don’t already use spam call blockers, you’ve almost certainly run into this situation before. In most cases, these are scam calls. Today, we explain why these calls happen, what the callers want from you, and how to protect yourself. Most importantly, we’ll look at whether you even need to bother protecting yourself against them in the first place. Who’s calling? It’s not just scammers on the line — robots, legitimate call center operators, and ordinary folks make these calls too. Let’s break down each type of caller — ordered from best-case to worst-case scenario for your security. Actual person The most harmless scenario is that an actual person called you, but their microphone is acting up. Maybe they accidentally muted themselves with their ear, or their smartphone connected to a Bluetooth headset, speaker, or car system that isn’t capturing their voice. Carrier glitches can also mute one side of a call. The caller might have no idea there’s a problem — as far as they know, they are speaking, but no one can hear them. In cases like this, you usually recognize the incoming phone number. If the call comes from an unknown number, there’s still no need to panic — though the list of those who might be calling gets much longer. One legitimate possibility is a call center agent who simply didn’t pick up or connect their headset in time. Call center systems are designed to dial numbers faster than agents can wrap up their calls. The system tried to route the call to a human, but no reps were available. That’s why you sometimes have to wait a few seconds before hearing a single word, or why you might hear ringing tones as if you were the one making the call. Robot or AI Silence on the line is a common sign of robocalls. Robots test whether a phone number is active and, if it is, pass it along to a human — meaning a real sales rep (or scammer) will call you back in the next few days. It’s worth noting that scammers aren’t the only ones making these pinging calls. Legitimate call centers use the exact same tools to reduce the workload on their live agents. An AI agent could also be behind the silent call. To the person answering, there’s no practical difference: the call looks identical to one made by a standard bot. However, AI can do more than just auto-dial numbers — it can analyze your response and use that data to decide whether your number is active and ready to be handed off to a live person for follow-up. Unwanted caller Now we get to the real threat. Perhaps one of the most dangerous and unpleasant sources of silent phone calls is a scammer. A quick, silent call like this can actually be the groundwork for a long, elaborate attack with cover stories about loans, government agencies, other fraudsters, even law enforcement. Debt collectors might also be calling and staying quiet. Your number could end up on their radar if you, your family, or close contacts have outstanding debts. In these cases, a silent call is often used as a tactic for psychological pressure. A similar technique is used in stalking. While silent calls cause no direct harm on their own, they can be leveraged to induce anxiety, create a feeling of being constantly watched, and cause ongoing emotional distress. Why do they call and stay silent? When you pick up, you likely respond out of habit with a quick “Hello?” or “Hi there.” That’s all it takes for the other party to gather a wealth of data. While this information used to be difficult to process, the rise of artificial intelligence has made the task significantly easier. Let’s look at what someone can learn about you from just one spoken word: Region, accent, and location. Scammers are sophisticated and cunning. Their tactics are often tailored by region — targeting residents of specific countries or even regions within them. This is especially relevant in places like In…

AI-Powered Analysis

Machine-generated threat intelligence

AILast updated: 07/30/2026, 11:04:41 UTC

Technical Analysis

This threat involves silent phone calls that are used primarily by scammers and robocallers to confirm active phone numbers and collect biometric voice data. The calls may be generated by automated systems, AI agents, or malicious actors. When a recipient answers and speaks, even briefly, AI can analyze vocal characteristics to infer demographic information and likelihood of engagement, which helps prioritize targets for follow-up scams. Attackers may use collected voice samples to create deepfake audio for impersonation in fraud schemes. While the calls themselves do not exploit a technical vulnerability, they facilitate social engineering attacks that can lead to financial or data loss.

Potential Impact

The direct impact of these silent calls is minimal as they do not exploit software vulnerabilities or cause immediate harm. However, they enable attackers to gather biometric voice data and behavioral information that can be used to craft convincing social engineering attacks, including voice deepfake scams. This can lead to financial fraud, unauthorized access, or emotional distress for victims targeted in follow-up attacks. The calls also increase the risk of being added to spam or scam call lists.

Defensive Guidance

There is no software patch or fix required for this threat. Users should avoid answering calls from unknown or hidden numbers, refrain from speaking first on suspicious calls, and block numbers that appear suspicious. Using call-blocking features on smartphones and maintaining separate phone numbers for different purposes can reduce exposure. Since this is a social engineering tactic rather than a software vulnerability, user awareness and cautious call handling are the primary defenses.

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Technical Details

Article Source
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Classification
{"confidence":0.3,"severitySource":"default","classifier":"rss-v2"}

Threat ID: 6a6b2fb29c2644c7f8f5c1a4

Added to database: 07/30/2026, 11:04:18 UTC

Last enriched: 07/30/2026, 11:04:41 UTC

Last updated: 09/13/2026, 08:01:08 UTC

Views: 83

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