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Google-IQ health - Google Analytics Individual Qualification (IQ) Updated: 2024

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Exam Code: Google-IQ Google Analytics Individual Qualification (IQ) health January 2024 by team

Google-IQ Google Analytics Individual Qualification (IQ)

Exam Detail:
The Google Analytics Individual Qualification (IQ) test is designed to assess an individual's knowledge and proficiency in using Google Analytics, a web analytics tool provided by Google. Here are the test details for the Google Analytics IQ exam:

- Number of Questions: The test typically consists of multiple-choice questions. The exact number of questions may vary, but it is typically around 70 questions.

- Time Limit: The time allotted to complete the test is 90 minutes (1 hour and 30 minutes).

Course Outline:
The Google Analytics IQ test covers a wide range of Topics related to Google Analytics and its various features. The course outline typically includes the following domains:

1. Fundamentals of Google Analytics:
- Understanding the basics of web analytics and its importance.
- Navigating the Google Analytics interface.
- Configuring Google Analytics accounts and properties.
- Setting up goals and conversion tracking.

2. Implementation and Data Collection:
- Implementing Google Analytics tracking code on websites.
- Configuring tracking parameters and custom dimensions.
- Understanding data collection methods and data accuracy.

3. Data Analysis and Reporting:
- Analyzing website traffic and user behavior using Google Analytics reports.
- Creating custom reports and segments.
- Understanding attribution modeling and cross-device tracking.
- Utilizing advanced features like data import, custom funnels, and event tracking.

4. Goals and Ecommerce Tracking:
- Setting up and tracking goals for different types of conversions.
- Configuring ecommerce tracking for online stores.
- Analyzing ecommerce performance and revenue attribution.

5. Campaign Tracking and Tag Management:
- Implementing campaign tracking using URL parameters and UTM tags.
- Utilizing tag management systems like Google Tag Manager.
- Understanding cross-domain and cross-device tracking.

Exam Objectives:
The objectives of the Google Analytics IQ test are as follows:

- Assessing candidates' understanding of web analytics principles and their application in Google Analytics.
- Evaluating candidates' proficiency in configuring and implementing Google Analytics tracking code.
- Testing candidates' ability to analyze and interpret data using Google Analytics reports and advanced features.
- Assessing candidates' knowledge of setting up goals, ecommerce tracking, and campaign tracking in Google Analytics.
- Evaluating candidates' understanding of tag management systems and their integration with Google Analytics.

Exam Syllabus:
The specific test syllabus for the Google Analytics IQ test covers the following topics:

1. Google Analytics Fundamentals:
- Introduction to web analytics and Google Analytics.
- Google Analytics account structure and navigation.
- Understanding basic metrics and dimensions.
- Setting up goals and ecommerce tracking.

2. Implementation and Data Collection:
- Installing and configuring the Google Analytics tracking code.
- Customizing tracking parameters and dimensions.
- Understanding data collection methods and data accuracy.

3. Data Analysis and Reporting:
- Analyzing standard reports and segments.
- Creating custom reports and advanced segments.
- Utilizing attribution modeling and cross-device tracking.
- Advanced features like data import and event tracking.

4. Goals and Ecommerce Tracking:
- Setting up and tracking goals for different types of conversions.
- Configuring ecommerce tracking for online stores.
- Analyzing ecommerce performance and revenue attribution.

5. Campaign Tracking and Tag Management:
- Implementing campaign tracking using URL parameters and UTM tags.
- Introduction to tag management systems and Google Tag Manager.
- Cross-domain and cross-device tracking.
Google Analytics Individual Qualification (IQ)
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Google Analytics Individual Qualification (IQ)
Question: 41 Section 18
Google Analytics uses which model by default when attributing conversion values in non-Multi-Channel Funnel
A. First Interaction model
B. Last Interaction model
C. Last Non-Direct Click model
D. Linear model
Answer: C
Question: 42 Section 18
Which of the following statements is true about Multi-Channel Funnel (MCF) reports?
A. You can create your own custom channel grouping in addition to the default MCF Channel grouping.
B. The channel labels that you see in Multi-Channel Funnels reports are defined as part of the MCF Channel
C. When you share a Custom Channel Grouping, only the configuration information is shared. Your data
remain private.
D. All of these statements are true.
Answer: D
Question: 43 Section 18
Which reporting dimension would be useful to reference if you were looking to Improve the user experience on
your landing pages?
A. Traffic type
B. Language
C. Device Category
D. B and C only
E. A, B, and C
Answer: D
Question: 44 Section 18
Auto-tagging is a feature that is used with which type of traffic?
A. Any search engine traffic that is not from Google
B. AdWords Campaign traffic
C. Website referrals
D. Social media referrals
Answer: B
Question: 45 Section 18
Google Analytics can identify that two sessions are from the same user if:
A. the sessions happen in the same browser on the same device
B. the sessions happen on the same day
C. the sessions happen in the same browser
D. the sessions occur within 30 minutes of each other
Answer: A
Question: 46 Section 18
When a report is based on data from a large number of sessions, you may see the following notice at the top of the
report: "This report is based on N sessions."
You can adjust the sampling rate of the report by:
A. changing the sampling rate in your view settings
B. adjusting the session timeout control
C. adjusting a control in the reporting interface for greater or less precision
D. You cannot adjust the demo data
Answer: C
Question: 47 Section 18
Segments are subsets of your Analytics data. Which of the following statements are NOT true of Analytics
A. Segments are filters that permanently change your data.
B. Segments let you isolate and analyze your data.
C. You can use segments to build custom Remarketing lists.
D. Segments represent either subsets of sessions or subsets of users.
Answer: A
Question: 48 Section 18
Why can AdWords clicks sometimes differ from Analytics sessions in your reports?
A. some visitors may have javascript disabled
B. some visitors may be blocking cookies
C. clicks and sessions are different metrics
D. all of the above
Answer: D
Question: 49 Section 18
What is an assisted conversion?
A. When one goal completion leads to another
B. When one traffic source results in a later goal completion through another traffic source
C. An AdWords view through conversion
D. When AdWords visitors returns to the site directly to convert
Answer: B
Question: 50 Section 18
What is an attribution model in Google Analytics?
A. the set of rules that determine which AdWords ads are credited with a conversion
B. the set of rules for assigning sessions to new vs returning users
C. the set of rules that determine how credit for sales and conversions is assigned to touchpoints in
conversion paths
D. the set of rules for assigning specific interest categories
Answer: C
Question: 51 Section 18
Adding filters to a view in Google Analytics allows you to:
A. exclude visits from a particular IP address
B. replace complicated page URLs with readable text strings
C. modify historical data
D. A and B only
E. A, B, and C
Answer: E
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Google Qualification health - BingNews Search results Google Qualification health - BingNews Google reveals the top 10 health searches of 2023 — and experts answer them No result found, try new keyword!Google has released its annual Year in Search, which breaks down the top searches in 2023. Below are the top 10 health-related questions of this year, along with experts’ responses to each. Thu, 28 Dec 2023 20:00:24 -0600 en-us text/html Google releases 2023 top health questions

(CNN)– Google has released its most searched health questions for 2023.

Number one searched health question is strep throat.

People asked questions like “How long is strep contagious?” And “How contagious is strep throat?”.

Other top searches include “How to lower cholesterol?”, and “What helps bloating?”.

Google says the questions were ones that saw high spikes in traffic over the past year compared to the previous year.

Sun, 31 Dec 2023 06:00:00 -0600 en-US text/html
Google swallows DeepMind Health

By Rory Cellan-JonesTechnology correspondent@BBCRoryCJ

The Streams app is saving nurses hours each day, the Royal Free Hospital says, but it proved controversial

Last November the pioneering London AI firm DeepMind announced that its health division was being transferred to its parent company Google.

Now, 10 months later, the move is finally happening, the delay a measure of how controversial and painful this process has been.

When the restructuring was announced last year, DeepMind was accused of breaking a promise not to hand over any NHS data to the American search giant.

Google said the transfer to its global health division would give DeepMind's Streams app, which helps doctors and nurses to monitor patients with a severe kidney condition, the resources it needed to expand internationally.

The Streams app had caused quite a stir when it was revealed that it used the data of about 1.6 million patients, without asking permission. The Information Commissioner's Office (ICO) ruled that the hospital involved in the research - the Royal Free in London - had not done enough to protect patient privacy.

And back in 2016, after controversy over the way NHS data was being used, DeepMind's co-founder Mustafa Suleyman made this pledge: "DeepMind operates autonomously from Google, and we've been clear from the outset that at no stage will patient data ever be linked or associated with Google accounts, products or services."

The end of that autonomy meant that Google had to renegotiate the contracts with NHS hospitals involved in DeepMind's research. It also mean the demise of the independent ethics panel which oversaw that research.

DeepMind was co-operating with Moorfields Eye Hospital, where it was working on using machine learning to assess eye scans with a high degree of accuracy, and with London's University College Hospital, where its technology was being tested in the planning of radiotherapy for patients with head and neck cancer.

Now Google says these and other NHS hospitals have, after lengthy discussions, decided to continue their collaborations. But one partner, the Yeovil District Hospital, which signed a five-year contract with DeepMind in 2017, decided not to transfer that deal to Google.

It told the BBC: "Working with the DeepMind team, we found that Streams is not necessary for our organisation at the current time."

In a blogpost, Dr Dominic King, who is taking a team of about a hundred from DeepMind to Google Health, explained why the transition had taken so long: "Health data is sensitive, and we gave proper time and care to make sure that we had the full consent and co-operation of our partners.

"This included giving them the time to ask questions and fully understand our plans and to choose whether to continue our partnerships. As has always been the case, our partners are in full control of all patient data and we will only use patient data to help Improve care, under their oversight and instructions."

But as of now there are no plans to replace the ethics panel, so there is little clarity on who will oversee the work Google does with the data of NHS patients. The staff are still in London - although they may have to move offices. Whether the work will stay in the UK for the long term remains to be seen.

Also unclear is where this leaves DeepMind and its co-founder Mustafa Suleyman. Last month it emerged that he had gone on long-term leave. The health division was his baby and, for all the high profile work around the AI firm's mastery of games like Go and chess, it was the most practical demonstration of how its technology could change the world.

He has released a statement saying he's "incredibly proud to reflect on the team's journey and achievements over the past three years, and I have no doubt that their positive impact will only increase as they join forces with Google Health".

He says he can't wait to see what comes next and looks forward to working with the team as "an advisor and supporter".

But insiders doubt he will have much influence over Google's health research when he returns from his extended break later this year.

DeepMind and its founders are rightly proud of their work in this field. But all their talk of operating as an autonomous UK-based AI powerhouse, with huge funding but little intervention from the Google mothership, now looks a little hollow.

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Wed, 18 Sep 2019 01:00:00 -0500 text/html 10 top-trending Google health searches of 2023

The world's most popular search engine can serve as a powerful reflection of our collective health concerns. 

Google released its 10 top-trending health questions that people searched from Jan. 1 to Nov. 27, 2023, reported by CNN. The "trending" queries are searches that had a high spike in traffic throughout a sustained period of time in 2023 compared to 2022, marking distinct shifts in the information people sought. 

The year's top searches for strep throat reflect a marked increase in the infections, for which emergency department visits reached a five-year high in February and March and remained high later in the year amid a monthslong shortage of amoxicillin. Questions about blood pressure, cholesterol and gastrointestinal disruptions also ranked highly. Some health Topics are noticeably missing from the top-trending searches in 2023, such as COVID-19 and mental health. 

Below are the top-trending health questions and concerns that people brought to Google throughout the year: 

1. How long is strep contagious?
2. How contagious is strep? 
3. How to lower cholesterol
4. What helps with bloating?
5. What causes low blood pressure?
6. What causes warts?
7. Why do I feel nauseous?
8. What causes preeclampsia?
9. How to stop snoring
10. How long does food poisoning last?

Fri, 29 Dec 2023 00:51:00 -0600 en-gb text/html
Google announces AI uses for health care market No result found, try new keyword!Google introduced a suite of AI health models "instead of trying to build a ‘one-size-fits-all’ solution," one company executive said. Tue, 19 Dec 2023 21:45:00 -0600 text/html Google accused of 'trust demolition' over health app

By Jane WakefieldTechnology reporter

The Streams app is saving nurses hours each day, the Royal Free Hospital says

A controversial health app developed by artificial intelligence firm DeepMind will be taken over by Google, it has been revealed.

Streams was first used to send alerts in a London hospital but hit headlines for gathering data on 1.6 million patients without informing them.

DeepMind now wants the app to become an AI assistant for nurses and doctors around the world.

One expert described the move as "trust demolition".

The news that Streams would be joining Google was announced in a DeepMind blogpost.

"Our vision is for Streams to now become an AI-powered assistant for nurses and doctors everywhere - combining the best algorithms with intuitive design, all backed up by rigorous evidence.

"The team working within Google, alongside brilliant colleagues from across the organisation, will help make this vision a reality."

It is not only Streams that will be affected. The DeepMind Health division, which now has a partnership with 10 NHS hospitals to process medical data, will also fall under the remit of California-based Google Health.

Lawyer and privacy expert Julia Powles, who has closely followed the development of Streams, responded on Twitter: "DeepMind repeatedly, unconditionally promised to 'never connect people's intimate, identifiable health data to Google'.

"Now it's announced... exactly that. This isn't transparency, it's trust demolition," she added.

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In response, DeepMind told the BBC: "Patient data remains under our NHS partners' strict control, and all decisions about its use will continue to lie with them. The move to Google does not affect this."

Streams began as a collaboration with the Royal Free Hospital in London to assist in the management of acute kidney injury. Doctors approached Google-owned DeepMind for help in developing software to help spot and alert clinicians about patients at risk.

Initially it did not use artificial intelligence, but still drew praise from the doctors and nurses using it because of the time it saved them in diagnosing and treating patients.

However, it emerged that neither the health trust nor DeepMind had informed patients about the vast amount of data it had been using.

DeepMind Health went on to work with Moorfields Eye Hospital, with machine-learning algorithms scouring images of eyes for signs of conditions such as macular degeneration.

In July 2017, the UK's Information Commissioner ruled the UK hospital trust involved in the initial Streams trial had broken UK privacy law for failing to tell patients about the way their data was being used.

It told the BBC that it expected that all the measures set out in its audit to "remain in place" after DeepMind Health moves to Google.

An independent review panel set up to scrutinise DeepMind's relationship with the NHS was "unlikely" to continue in its current form, given the US takeover of the health division, DeepMind confirmed to the BBC.

It is not the first time an independent firm has been subsumed by Google.

Nest, which collects data from home security cameras, thermostats and doorbells, was set up as a stand-alone, with promises that no data would be shared with the search giant.

But in February it was merged with Google to help build "a more thoughtful home".

Copyright 2024 BBC. All rights reserved.  The BBC is not responsible for the content of external sites. Read about our approach to external linking.

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In case of conflict between these Beta Terms and the BBC Terms of Use these Beta Terms shall prevail.

Tue, 13 Nov 2018 22:05:00 -0600 text/html Google is rolling out new AI models for health care. Here's how doctors are using them
  • Google on Wednesday announced a suite of new health-care AI models called MedLM.
  • The move marks Google's latest attempt to monetize health-care industry AI tools, as competition for market share remains fierce between competitors like Amazon and Microsoft. 
  • Google said it plans to introduce health-care-specific versions of Gemini, the company's existing and "most capable" AI model, to MedLM in the future.

Google on Wednesday announced MedLM, a suite of new health-care-specific artificial intelligence models designed to help clinicians and researchers carry out complex studies, summarize doctor-patient interactions and more.

The move marks Google's latest attempt to monetize health-care industry AI tools, as competition for market share remains fierce between competitors like Amazon and Microsoft. CNBC spoke with companies that have been testing Google's technology, like HCA Healthcare, and experts say the potential for impact is real, though they are taking steps to implement it carefully.

The MedLM suite includes a large and a medium-sized AI model, both built on Med-PaLM 2, a large language model trained on medical data that Google first announced in March. It is generally available to eligible Google Cloud customers in the U.S. starting Wednesday, and Google said while the cost of the AI suite varies depending on how companies use the different models, the medium-sized model is less expensive to run. 

Google said it also plans to introduce health-care-specific versions of Gemini, the company's existing and "most capable" AI model, to MedLM in the future.

Aashima Gupta, Google Cloud's global director of health-care strategy and solutions, said the company found that different medically tuned AI models can carry out certain tasks better than others. That's why Google decided to introduce a suite of models instead of trying to build a "one-size-fits-all" solution. 

For instance, Google said its larger MedLM model is better for carrying out complicated tasks that require deep knowledge and lots of compute power, such as conducting a study using data from a health-care organization's entire patient population. But if companies need a more agile model that can be optimized for specific or real-time functions, such as summarizing an interaction between a doctor and patient, the medium-sized model should work better, according to Gupta.

Real-world use cases

Krisztian Bocsi | Bloomberg | Getty Images

A Google Cloud logo at the Hannover Messe industrial technology fair in Hanover, Germany, on Thursday, April 20, 2023.

When Google announced Med-PaLM 2 in March, the company initially said it could be used to answer questions like "What are the first warning signs of pneumonia?" and "Can incontinence be cured?" But as the company has tested the technology with customers, the use cases have changed, according to Greg Corrado, head of Google's health AI. 

Corrado said clinicians don't often need help with "accessible" questions about the nature of a disease, so Google hasn't seen much demand for those capabilities from customers. Instead, health organizations often want AI to help solve more back-office or logistical problems, like managing paperwork.  

"They want something that's helping them with the real pain points and slowdowns that are in their workflow, that only they know," Corrado told CNBC. 

For instance, HCA Healthcare, one of the largest health systems in the U.S., has been testing Google's AI technology since the spring. The company announced an official collaboration with Google Cloud in August that aims to use its generative AI to "improve workflows on time-consuming tasks." 

Dr. Michael Schlosser, senior vice president of care transformation and innovation at HCA, said the company has been using MedLM to help emergency medicine physicians automatically document their interactions with patients. For instance, HCA uses an ambient speech documentation system from a company called Augmedix to transcribe doctor-patient meetings. Google's MedLM suite can then take those transcripts and break them up into the components of an ER provider note.

Schlosser said HCA has been using MedLM within emergency rooms at four hospitals, and the company wants to expand use over the next year. By January, Schlosser added, he expects Google's technology will be able to successfully generate more than half of a note without help from providers. For doctors who can spend up to four hours a day on clerical paperwork, Schlosser said saving that time and effort makes a meaningful difference. 

"That's been a huge leap forward for us," Schlosser told CNBC. "We now think we're going to be at a point where the AI, by itself, can create 60-plus percent of the note correctly on its own before we have the human doing the review and the editing." 

Schlosser said HCA is also working to use MedLM to develop a handoff tool for nurses. The tool can read through the electronic health record and identify relevant information for nurses to pass along to the next shift. 

Handoffs are "laborious" and a real pain point for nurses, so it would be "powerful" to automate the process, Schlosser said. Nurses across HCA's hospitals carry out around 400,000 handoffs a week, and two HCA hospitals have been testing the nurse handoff tool. Schlosser said nurses conduct a side-by-side comparison of a traditional handoff and an AI-generated handoff and provide feedback.

With both use cases, though, HCA has found that MedLM is not foolproof.

Schlosser said the fact that AI models can spit out incorrect information is a big challenge, and HCA has been working with Google to come up with best practices to minimize those fabrications. He added that token limits, which restrict the amount of data that can be fed to the model, and managing the AI over time have been additional challenges for HCA. 

"What I would say right now, is that the hype around the current use of these AI models in health care is outstripping the reality," Schlosser said. "Everyone's contending with this problem, and no one has really let these models loose in a scaled way in the health-care systems because of that."

Even so, Schlosser said providers' initial response to MedLM has been positive, and they recognize that they are not working with the finished product yet. He said HCA is working hard to implement the technology in a responsible way to avoid putting patients at risk.

"We're being very cautious with how we approach these AI models," he said. "We're not using those use cases where the model outputs can somehow affect someone's diagnosis and treatment."

Getty Images

Google also plans to introduce health-care-specific versions of Gemini to MedLM in the future. Its shares popped 5% after Gemini's launch earlier this month, but Google faced scrutiny over its demonstration video, which was not conducted in real time, the company confirmed to Bloomberg

In a statement, Google told CNBC: "The video is an illustrative depiction of the possibilities of interacting with Gemini, based on real multimodal prompts and outputs from testing. We look forward to seeing what people create when access to Gemini Pro opens on December 13."

Corrado and Gupta of Google said Gemini is still in early stages, and it needs to be tested and evaluated with customers in controlled health-care settings before the model rolls out through MedLM more broadly. 

"We've been testing Med-PaLM 2 with our customers for months, and now we're comfortable taking that as part of MedLM," Gupta said. "Gemini will follow the same thing." 

Schlosser said HCA is "very excited" about Gemini, and the company is already working out plans to test the technology, "We think that may give us an additional level of performance when we get that," he said.

Another company that has been using MedLM is BenchSci, which aims to use AI to solve problems in drug discovery. Google is an investor in BenchSci, and the company has been testing its MedLM technology for a few months.  

Liran Belenzon, BenchSci's co-founder and CEO, said the company has merged MedLM's AI with BenchSci's own technology to help scientists identify biomarkers, which are key to understanding how a disease progresses and how it can be cured. 

Belenzon said the company spent a lot of time testing and validating the model, including providing Google with feedback about necessary improvements. Now, Belenzon said BenchSci is in the process of bringing the technology to market more broadly.  

"[MedLM] doesn't work out of the box, but it helps accelerate your specific efforts," he told CNBC in an interview. 

Corrado said research around MedLM is ongoing, and he thinks Google Cloud's health-care customers will be able to tune models for multiple different use cases within an organization. He added that Google will continue to develop domain-specific models that are "smaller, cheaper, faster, better."  

Like BenchSci, Deloitte tested MedLM "over and over" before deploying the technology to health-care clients, said Dr. Kulleni Gebreyes, Deloitte's U.S. life sciences and health-care consulting leader.

Deloitte is using Google's technology to help health systems and health plans answer members' questions about accessing care. If a patient needs a colonoscopy, for instance, they can use MedLM to look for providers based on gender, location or benefit coverage, as well as other qualifiers. 

Gebreyes said clients have found that MedLM is accurate and efficient, but, like other models, the AI is not always great at deciphering a user's intent. It can be a challenge if patients don't know the right word or spelling for colonoscopy, or use other colloquial terms, she said. 

"Ultimately, this does not substitute a diagnosis from a trained professional," Gebreyes told CNBC. "It brings expertise closer and makes it more accessible."

Tue, 12 Dec 2023 10:00:00 -0600 en-US text/html
Hackers discover way to access Google accounts without a password

Security researchers have uncovered a hack that allows cyber criminals to gain access to people’s Google accounts without needing their passwords.

Analysis from security firm CloudSEK found that a dangerous form of malware uses third-party cookies to gain unauthorised access to people’s private data, and is already being actively tested by hacking groups.

The exploit was first revealed in October 2023 when a hacker posted about it in a channel on the messaging platform Telegram.

The post noted how accounts could be compromised through a vulnerability with cookies, which are used by websites and browsers to track users and increase their efficiency and usability.

Google authentification cookies allow users to access their accounts without constantly having to enter their login details, however the hackers found a way to retrieve these cookies in order to bypass two-factor authentication.

The Google Chrome web browser, which is the world’s most popular with a market share greater than 60 per cent last year, is currently in the process of cracking down on third-party cookies.

“We routinely upgrade our defences against such techniques and to secure users who fall victim to malware. In this instance, Google has taken action to secure any compromised accounts detected,” Google said in a statement.

“Users should continually take steps to remove any malware from their computer, and we recommend turning on Enhanced Safe Browsing in Chrome to protect against phishing and malware downloads.”

The researchers who first uncovered the threat said it “underscores the complexity and stealth” of modern cyber attack.

“This exploit enables continuous access to Google services, even after a user’s password is reset,” Pavan Karthick M, a threat intelligence researcher at CloudSEK, wrote in a blog post detailing the issue.

“It highlights the necessity for continuous monitoring of both technical vulnerabilities and human intelligence sources to stay ahead of emerging cyber threats.”

The security issue was detailed in a report, titled ‘Compromising Google accounts: Malwares Exploiting Undocumented OAuth2 Functionality for session hijacking’, written by CloudSEK threat intelligence researcher Pavan Karthick M.

Thu, 04 Jan 2024 05:02:00 -0600 en-US text/html

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