In recent years, spam in calls, SMS, email and messaging It has become a real headache for users, businesses, and operators. What began as somewhat annoying advertising has transformed into a security problem, a loss of money, and a saturation of communications infrastructure. Today, defending against spam requires a intelligent filtering of communicationssupported by regulation, advanced technology and good practices.
At the same time, filtering tools have been getting more sophisticated: from simple blacklists to solutions with Artificial Intelligencebehavioral analysis and identity verificationIn this article you will find a complete and well-organized overview of how spam works on different channels (voice, SMS, email), how modern filters combat it, what regulations require in Spain and other countries, and what both companies (especially call centers and operators) and users can do to minimize its impact.
Why spam is a serious problem for users and businesses
Intrusive advertising is no longer just a nuisance: Spam affects efficiency, privacy, and securityIn the case of call centers that rely on telephony, the contact rate is the metric that determines the profitability of campaigns. This is especially true when using filters from operators or apps like Truecaller or Hiya. They mark a number as "spam" or "fraud," many calls don't even ring or are automatically rejected, wasting the investment in platforms, data, and agents.
From the end user's point of view, the scenario is not promising either: the persistent calls, the Promotional SMS and spam They are time-consuming, generate distrust, and can open the door to scams, phishing, or malware installation. Global figures show that more than half of worldwide email traffic has been spam during certain periods, with the resulting strain on networks, servers, and users.
Furthermore, spam has become more "professionalized." We're no longer just talking about heavy-handed marketing messages: Organized gangs use mass campaigns to launch scams, impersonate others (spoofing), or distribute links to infected websites. This is why data protection and telecommunications authorities have begun to tighten regulations and require companies and operators to implement technical defense measures.
Telephone spam and commercial calls: legal framework and new obligations
In Spain, unsolicited commercial calls are regulated, among other rules, by the General Telecommunications Law and the General Law for the Defense of Consumers and UsersThese laws recognize the right not to receive calls for advertising purposes without prior consent, or without a real and justified legitimate interest.
The Spanish Data Protection Agency has made it clear that Legitimate interest is no excuse To call random numbers, people registered on advertising opt-out schemes, or those who have already opted out, the business owner must identify themselves at the beginning of the call, explicitly explain the commercial purpose, and respect time slots: no calls outside of 9:00 a.m. to 21:00 p.m., nor on weekends or holidays.
In parallel, specific rules have been introduced regarding numbering and identification of business callsThe use of mobile phones for unsolicited telemarketing is restricted, and the use of identifiable number ranges (geographic, 800, 900, or other specifically assigned ranges) is mandatory to improve traceability and curb fraud. From certain dates, some countries require that commercial calls originate from specific prefixes (such as those beginning with 400), making it easier for users to know in advance if they are receiving advertising.
If the consumer detects commercial calls from numbers that do not meet these criteria—for example, mobile phones that look like they belong in a home or unassigned numbers—they can Inform your operator or report to the competent authority, such as the AEPD in Spain, which can initiate sanctioning procedures.
Advertising opt-out lists and consent management
One of the most effective mechanisms for reducing commercial spam is to use advertising opt-out recordsIn Spain, the best known is the Robinson List, a free service where anyone can register their phone number, email address, postal address, or even select specific companies and channels they do not want to receive messages from.
Upon registering, companies wishing to launch marketing campaigns are required to consult the list and exclude registered individualsUnless there is subsequent valid and specific consent. If, despite being registered, the user continues to receive advertising without having authorized it, they can file a complaint with the Spanish Data Protection Agency (AEPD). From 2025, the STOP Advertising List, also approved by the AEPD, will be added, expanding blocking options across different channels and allowing users to register multiple phone numbers and addresses in the same record.
Beyond opt-out lists, consent is often obtained through fine print. Registration forms, contests, discounts, and promotions frequently include it. advertising acceptance boxes, sometimes pre-ticked or unclearly wordedThe user has the right not to tick these boxes and, if they have already accepted them, to withdraw their consent at any time through the channel enabled by the company (email, web form, etc.).
Data protection regulations also recognize specific rights: the right of cancellation or deletionwhich allows you to request the deletion of data when it is no longer necessary for the original purpose, and the right of oppositionThis is key to blocking the use of data for direct marketing or commercial profiling. If companies do not respect these decisions, users can resort to mediation systems such as Autocontrol or directly to the Spanish Data Protection Agency (AEPD).
User protection: identify, block and filter calls and messages
Faced with the bombardment of calls and messages, users increasingly have more smart filtering tools on your devicesOn Android phones that use the Google Phone app, there is an integrated caller ID and spam protection system that is activated by default on many models.
When a call comes in from an unknown number, the phone queries Google's servers—without uploading the user's contact list—to determine if the number is associated with telemarketing, aggressive advertising, or potential fraudIf it deems a call suspicious, it may display warnings such as "Spam" or "Suspected of spam" on the screen. Depending on the settings, these calls are either flagged, muted, or filtered so that the phone doesn't even ring.
The user can also manually strengthen this protection. This can be done from the call log. block a number and mark it as spam This ensures that future calls are automatically rejected but still appear in the call history and, if applicable, in the voicemail. Conversely, if the system labels a legitimate call as spam, it can be marked as "Not spam" to correct the error and avoid false positives.
In the area of ​​email and messaging, current customers incorporate smart filters which divert messages that appear dangerous or promotional to a spam folder. Even so, many users choose to mark emails as spam or directly block offensive or suspicious senders And, on platforms like WhatsApp, report accounts that abuse the mass sending of promotions or attempted scams.
Advanced mobile solutions: Google and Apple call filters
Major mobile operating system manufacturers have taken several further steps in the fight against phone spam, integrating tools for call screening or proactive filtering directly in the system.
On Google Pixel devices, the Assistant's Call Filter allows a virtual assistant to answer calls from unknown numbers. This automated voice asks the caller to identify themselves and explain the reason for the call, while the screen displays... a real-time transcript of the conversationFrom there, the user can decide whether to reply, hang up, mark the number as spam, or request more information without having to say a word.
In the latest models, this filtering can be configured to automatically apply to certain categories of suspicious calls, drastically reducing the amount of spam reaching the user. And, in other Android devices that use the Google Phone app, while not offering the same level of automation, they do provide advanced options for silence and block unknown or potentially fraudulent calls.
For its part, Apple has reinforced its commitment with new versions of iOS that include Call Filtering features and smarter SMS and message management. iMessage, for example, distinguishes known senders of unknown numbersrelegating the latter to secondary inboxes without notification, which reduces the impact of promotional messages and smishing (SMS phishing).
How call centers combat spam labeling
For call centers, the biggest enemy isn't just that people are tired of advertising, but that Phone detection algorithms classify your numbers as spamWhen this happens, campaigns instantly lose profitability. The key here is to understand that these systems don't analyze the content of the calls, but rather behavioral patterns: volume, frequency, duration, abandonment rates, etc.
A single number making a massive volume of calls in a short time is interpreted as automatic dialing or robocallThis is especially true if many calls are answered and hung up within seconds, or if the user perceives the call as harassment and reports it through apps or the operator's own system. Therefore, modern call center strategies focus on appearing—and being—as human and reasonable as possible in their dialing practices.
Among the critical factors are: avoiding disproportionate traffic spikes on the same number, reduce repetitive attempts in a short interval, control the rates of "short" or abandoned calls and adjust the logic of predictive dialers so that there are always agents available when the customer picks up.
At the same time, data hygiene becomes fundamental: user complaints carry significant weight in reputation systems, so "Do Not Call" requests must be scrupulously respected, the database must be cleaned to remove inactive or non-responsive numbers, and synchronization must be implemented. CRM, Robinson lists and internal exclusion lists to avoid inappropriate contact.
Intelligent Number Rotation (CNAM) and CLI Management in VoIP
One of the most effective techniques to reduce the risk of being labeled as spam on VoIP platforms like Asterisk is to implement intelligent rotation of caller ID (CLI) and display name (CNAM)Instead of concentrating all activity on a single number, we work with a "pool" of numbers that alternate.
This approach involves creating a dynamic set of numbers—geographic landlines, 800/900 numbers, or other ranges authorized according to local regulations—and configuring it so that each new outgoing call uses the least used number or the number that has been idle the longestIt can be implemented with simple round-robin distributions or with more complex logic that queries a recently used database.
The concept of "cooling down" is key: when a number has handled a significant volume of calls, it is temporarily removed from the active pool so that Its reputation recovers in the face of the filters of the operators and the appsIn parallel, logging and monitoring systems are integrated that detect when a number begins to show signs of penalty (low contact rate, increased rejections, spam reports) and remove it from traffic until further notice.
Thanks to the flexibility of platforms like Asterisk, this rotation can be orchestrated directly from the dialplan, connecting with databases, CRMs, and analytical tools to optimize the use of the numbering pool in real time and minimize the impact of automatic filters.
Identity certification and future anti-fraud standards
Beyond behavioral patterns, authorities and operators are evolving towards systems of caller's identity verificationIn North America, the STIR/SHAKEN standard has already become mandatory to authenticate that the call really comes from the number that appears on the screen, making spoofing more difficult.
In Europe, regulations are still under development, but the trend points to models where the caller's identity is verified by the operator, assigning different levels of trust to the CLI. For call centers, this means working closely with their provider of SIP Trunking to formally register your numbers as legitimate lines of business and ensure that the VoIP infrastructure supports the necessary headers and tokens.
At the same time, transparency becomes an indispensable requirement: the CNAM that is sent must correspond to the legal or campaign name that the user recognizes and with the type of service offered. Consistency between what the recipient sees on the screen, who is behind the number, and the reason for the call is one of the most important factors in building trust and reducing both immediate rejection and complaints.
In other countries, complementary measures are being promoted: centralized databases for mitigating robocalls, "voice firewall" solutions that block suspicious patterns on the operators' network, or strict requirements for logging incoming and outgoing traffic. detect anomalous behavior at the network level.
Intelligent call filtering at the carrier level
While users are using apps and call centers are adjusting their practices, telecom operators are beginning to deploy services of intelligent call filtering at network scaleSolutions like those offered by certain providers allow the operator to block or divert suspicious calls before they reach the terminal.
These types of platforms analyze incoming call signaling, checking the CLI, country of origin, numbering patterns, frequency, and other technical data to locate indicators of spam, fraud or spoofingWhen a threat is detected, the call can be blocked, dialed, or diverted to automated systems that collect information without disturbing the user.
Some solutions introduce a smart voicemail managed by conversational AI that asks the caller the reason for the call, extracts key data, and generates a summary that is sent to the user via email or SMS. This way, the customer avoids answering annoying calls, but Continue to receive important information if it was a legitimate communication. In practice, it's like having a virtual secretary that filters and prioritizes traffic.
Unlike third-party apps based on static databases and user reports, the operator's approach can combine information from its own network, external reputation databases, customer contact lists (respecting privacy), and internal APIs. This achieves a a much faster response to new attacksFor example, numbering rotations in automated fraud campaigns, where public blacklists take time to react.
Email spam filtering: classic and modern techniques
Email remains one of the preferred channels for spam, both in terms of volume and potential for fraud. Current filters employ a combination of complementary methods for classifying messages and decide whether they should go to the inbox, the spam folder, or be blocked directly.
Content filters examine text for words and patterns typical of spam, such as "limited offer," "amazing discount," "free," or terms related to recurring scams. They also take into account excessive use of capital letters, exclamation marks, explicit language, or suspicious structuresIn addition, there are header filters, which check the technical headers of the message to detect suspicious IPs, discrepancies between domains, inconsistencies in sender fields, or unusual sending routes.
Blacklists play another key role: they collect IP addresses and domains associated with mass spam mailingsIf an organization's mail server ends up being blacklisted—for example, because an infected computer becomes a "zombie" and sends malicious email without anyone noticing—legitimate messages will also start bouncing or being filtered as spam.
Along with these mechanisms, many systems allow users to create rules based on keywords, senders, domains, or message sizes to automatically direct certain emails to specific folders or mark them as spam. It's a more manual approach, but very useful for tailoring filtering to the needs of each individual or company.
Bayesian filters, machine learning, and email zombies
Bayesian filters were one of the major advances in the fight against spam, as they are based on probabilities calculated from real examplesWhen a user marks a message as spam or legitimate, the system learns which words, structures, and patterns are associated with each category, progressively refining its decisions.
These approaches have their limitations and can produce false positives (good emails ending up in spam) or false negatives (spam slipping through), but when combined with other techniques they are very effective. The natural evolution is systems based on more advanced machine learning, which analyze large volumes of data from millions of users to detect trends and new types of threats more quickly.
One particularly critical problem for businesses is the formation of zombie networks within its own infrastructureA computer infected with malware can start sending spam emails without anyone noticing, damaging the company's IP reputation. Dedicated outbound anti-spam services allow you to monitor and stop this traffic, protecting both third parties and the company's ability to send legitimate emails without being blacklisted.
In this context, Internet service providers and large corporations typically deploy their own filters at the network and server levels. While they may occasionally filter legitimate messages, most offer fine-tuning options and whitelists so that users can authorize trusted domains and senders, reducing the likelihood of missing important communications.
With this entire ecosystem of laws, device filters, carrier solutions, advanced VoIP platforms, and email tools, spam defense has become a multi-layered strategy where each actor has their role: the user who manages their consent and blocks suspicious calls, the company that takes care of its business practices and reputation, and the operators and technology providers who put in place the infrastructure and intelligence necessary to make communications, as far as possible, useful, secure, and free of unnecessary noise.
