9 types of phishing attacks and how to identify them
Different victims, different paydays. A phishing attack specifically targeting
an enterprise’s top executives is called whaling, as the victim is considered to
be high-value, and the stolen information will be more valuable than what a
regular employee may offer. The account credentials belonging to a CEO will open
more doors than an entry-level employee. The goal is to steal data, employee
information, and cash. ... Clone phishing requires the attacker to create a
nearly identical replica of a legitimate message to trick the victim into
thinking it is real. The email is sent from an address resembling the legitimate
sender, and the body of the message looks the same as a previous message. The
only difference is that the attachment or the link in the message has been
swapped out with a malicious one. ... Snowshoeing, or “hit-and-run” spam,
requires attackers to push out messages via multiple domains and IP addresses.
Each IP address sends out a low volume of messages, so reputation- or
volume-based spam filtering technologies can’t recognize and block malicious
messages right away. Some of the messages make it to the email inboxes before
the filters learn to block them.
The End Of The SaaS Era: Rethinking Software’s Role In Business
While the traditional SaaS model may be losing its luster, software itself
remains a critical component of modern business operations. The key shift is
in how companies think about and utilize software. Rather than viewing it as a
standalone business model, forward-thinking entrepreneurs and executives are
beginning to see software as a powerful tool for creating value in other
business contexts. ... Consider a hypothetical scenario where a tech company
develops an AI-powered inventory management system that dramatically improves
efficiency for retail businesses. Instead of simply selling this system as a
SaaS product, the company could use it as leverage to acquire successful
retail operations. By implementing their proprietary software, they could
significantly boost the profitability of these businesses, creating value far
beyond what they might have captured through traditional software licensing.
... Proponents of this new approach argue that while others will eventually
catch up in terms of software capabilities, the first-movers will have already
used their technological edge to acquire valuable real-world assets.
How Agentless Security Can Prevent Major Ops Outages
An agentless security model is a modern way to secure cloud environments
without installing agents on each workload. It uses cloud providers’ native
tools and APIs to monitor and protect assets like virtual machines, containers
and serverless functions. Here’s how it works: Data is collected through API
calls, providing real-time insights into vulnerabilities. A secure proxy
ensures seamless communication without affecting performance. This model
continuously scans workloads, offering 100% visibility and detecting issues
without disruption. ... Instead of picking between agent-based and agentless
security, you can use both together. Agent-based security works best for
stable, less-changing systems. It offers deep, ongoing monitoring when things
stay the same. On the other hand, agentless security is great for fast-paced
cloud setups where new workloads come and go often. It gives real-time
insights without needing to install anything, making it flexible for larger
cloud systems. A hybrid approach gives you stronger protection and keeps up
with changing threats, making sure your defenses are ready for whatever comes
next.
The inner workings of a Conversational AI
The initial stage of interaction between a user and an AI system involves
input processing. When a user submits a prompt, the system undergoes a series
of preprocessing steps to transform raw text into a structured format suitable
for machine comprehension. Natural Language Processing (NLP) techniques are
employed to break down the text into individual words or tokens, a process
known as tokenization. ... Once the system has a firm grasp of the user’s
intent through input processing, it embarks on the crucial phase of knowledge
retrieval. This involves sifting through vast repositories of information to
extract relevant data. Traditional information retrieval techniques like BM25
or TF-IDF are employed to match the processed query with indexed documents. An
inverted index, a data structure mapping words to the documents containing
them, accelerates this search process. ... With relevant information gathered,
the system transitions to the final phase: response generation. This involves
constructing a coherent and informative text that directly addresses the
user’s query. Natural Language Generation (NLG) techniques are employed to
transform structured data into human-readable language.
Can We Ever Trust AI Agents?
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The consequences of misplaced trust in AI agents could be dire. Imagine an
AI-powered financial advisor that inadvertently crashes markets due to a
misinterpreted data point, or a healthcare AI that recommends incorrect
treatments based on biased training data. The potential for harm is not
limited to individual sectors; as AI agents become more integrated into our
daily lives, their influence grows exponentially. A misstep could ripple
through society, affecting everything from personal privacy to global
economics. At the heart of this trust deficit lies a fundamental issue:
centralization. The development and deployment of AI models have largely been
the purview of a handful of tech giants. ... The tools for building trust in
AI agents already exist. Blockchains can enable verifiable computation,
ensuring that AI actions are auditable and traceable. Every decision an AI
agent makes could be recorded on a public ledger, allowing for unprecedented
transparency. Concurrently, advanced cryptographic techniques like trusted
execution environment machine learning (TeeML) can protect sensitive data and
maintain model integrity, achieving both transparency and privacy.
Reducing credential complexity with identity federation
One potential challenge organizations may encounter when implementing
federated identity management in cross-organization collaborations is ensuring
a seamless trust relationship between multiple identity providers and service
providers. If the trust isn’t well established or managed, it can lead to
security vulnerabilities or authentication issues. Additionally, the
complexity of managing multiple identity providers can become problematic if
there is a need to merge user identities across systems. For example, ensuring
that all identity providers fulfill their roles without conflicting or
creating duplicate identities can be challenging. Finally, while federated
identity management improves convenience, it can come at the cost of
time-consuming engineering and IT work to set up and maintain these IdP-SP
connections. Traditional in-house implementation may also mean these
connections are 1:1 and hard-coded, which will make ongoing modifications even
tougher. Organizations need to balance the benefits of federated identity
management against the time and cost investment needed, whether they do it
in-house or with a third-party solution.
AI: Maximizing innovation for good
Businesses need to understand that AI technology will be here to stay. Strong
AI strategies consider the purpose and objectives of considering AI,
explaining the processes for businesses to prove value and absorb the rapid
pace of change, considering the technology itself. Implementation needs to
ensure that solutions mesh effectively with IT infrastructure that’s already
in place. Digitalization, digital transformation, and upgrading legacy
systems, as overarching initiatives, require planning and understanding of how
they will impact wider business functions. That’s not to say it needs to be
slow or cumbersome, however – one of the joys on AI is the ease with which it
can put powerful new capabilities in the hands of teams. When due diligence is
conducted effectively, AI integration can become the lynchpin to elevate
business practices – boosting productivity, efficiency, and lowering costs.
The opportunities for improvements cannot be understated, especially when
looking at wider settings outside of just industrial or financial sectors.
Ultimately, overreaching when implementing AI, can create a situation where
integrated tools muddy the water and dilute the effectiveness of their
intended use.
The Path of Least Resistance to Privileged Access Management
While PAM allows organizations to segment accounts, providing a barrier
between the user’s standard access and needed privileged access and
restricting access to information that is not needed, it also adds a layer of
internal and organizational complexity. This is because of the impression it
removes user’s access to files and accounts that they have typically had the
right to use, and they do not always understand why. It can bring changes to
their established processes. They don’t see the security benefit and often
resist the approach, seeing it as an obstacle to doing their jobs and causing
frustration amongst teams. As such, PAM is perceived to be difficult to
introduce because of this friction. ... A significant gap in the PAM
implementation process lies in the lack of comprehensive awareness among
administrators. They often do not have a complete inventory of all accounts,
the associated access levels, their purposes, ownership, or the extent of the
security issues they face. Although PAM solutions possess the capability for
scanning and discovering privileged accounts, these solutions are limited by
the scope of the instructions they receive, thus providing only partial
visibility into system access and usage.
Microsoft researchers propose framework for building data-augmented LLM applications
“Data augmented LLM applications is not a one-size-fits-all solution,” the
researchers write. “The real-world demands, particularly in expert domains,
are highly complex and can vary significantly in their relationship with given
data and the reasoning difficulties they require.” To address this complexity,
the researchers propose a four-level categorization of user queries based on
the type of external data required and the cognitive processing involved in
generating accurate and relevant responses: – Explicit facts: Queries that
require retrieving explicitly stated facts from the data. – Implicit facts:
Queries that require inferring information not explicitly stated in the data,
often involving basic reasoning or common sense. – Interpretable rationales:
Queries that require understanding and applying domain-specific rationales or
rules that are explicitly provided in external resources. – Hidden rationales:
Queries that require uncovering and leveraging implicit domain-specific
reasoning methods or strategies that are not explicitly described in the data.
Each level of query presents unique challenges and requires specific solutions
to effectively address them.
Unleashing the Power Of Business Application Integration
In many cases, businesses are replacing their legacy software solutions with a
modular selection of applications hosted within a public cloud environment.
Given the increasing maturity of this market, there is now a range of
application stores and marketplaces from the likes of AWS, Microsoft and
Google. These have made it much easier for IT teams to identify, purchase and
integrate proven applications as part of a bespoke, enterprise-wide ERP
strategy. ... once IT teams have selected and integrated the right business
applications within their environment, the next step is to focus on data
strategy. The main objective here should be to ensure that data is of the
highest quality and can be used to address a diverse range of key business
objectives, from driving profit, efficiency and innovation to improving
customer service. This process can be complex and challenging, but there are a
number of steps organisations can take to fully exploit their data assets.
These include optimising the performance and availability of an existing data
environment and prioritising data systems migration.
Quote for the day:
"The first step toward success is
taken when you refuse to be a captive of the environment in which you first
find yourself." -- Mark Caine
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